quality of service based admission control for wcdma mobile
TRANSCRIPT
HELSINKI UNIVERSITY OF TECHNOLOGY
Department of Engineering Physics and Mathematics
Janne Pöllönen
Quality of Service Based Admission Control for
WCDMA Mobile Systems
Master’s thesis submitted in partial fulfillment of the requirements for
the degree of Master of Science in Technology
Espoo, 13.11.2001
Supervisor: Professor Raimo P. Hämäläinen
Instructor: M.Sc. Albert Höglund
HELSINKI UNIVERSITY OF TECHNOLOGY Abstract of Master’s Thesis
Author: Janne Pöllönen
English title: Quality of Service Based Admission Control for WCDMA
Mobile Systems Finnish title: Laatuperustainen pääsynvalvonta WCDMA mobiiliverkoissa
Date: 13th November, 2001 Pages: 66
Department: Department of Engineering Physics and Mathematics
Chair: Mat-2 Applied Mathematics
Supervisor: Professor Raimo P. Hämäläinen
Instructor: M.Sc. Albert Höglund
Abstract:
The performance of DS-CDMA cellular radio networks, such as UMTS, is highly dependent on the amount of interference in the system. High interference reduces cell size and increases the outage probability of mobile users. Interference is increased as the number of admitted users grows in the system. This means that there is a trade-off between capacity and coverage and between capacity and quality of service (QoS).
The system load is controlled by the radio resource management (RRM). The optimization and adaptivity of RRM is of great importance both for the operators and for manufacturers, since RRM has a lot to answer for when it comes to the stability and the utilized capacity of mobile network.
In this thesis, uplink admission control and closely related concepts such as CDMA and RRM are studied. The focus is on interference based admission control. A strategy to improve the system effectiveness in terms of QoS, by tuning the threshold limiting the total amount of received uplink power, is proposed.
The impact of the proposed autotuning algorithm on the system performance is investigated by system simulations. Both real time circuit switched speech traffic and non-real time interactive packet traffic is studied. The quality indicators used are call blocking probability, bad call probability and call dropping probability. These quality indicators are combined in a cost function to provide the metrics to evaluate the overall cell performance.
The conducted simulations support the assumption that the uplink performance can be improved by the proposed autotuning feature. Possible challenges and implementation related details that need to be solved are pointed out.
Keywords: WCDMA, interference, UMTS, radio resource management,
admission control, quality of service
TEKNILLINEN KORKEAKOULU Diplomityön tiivistelmä
Tekijä: Janne Pöllönen
Otsikko: Laatupohjainen pääsynvalvonta WCDMA mobiiliverkoissa
English title: Quality of Service Based Admission Control for WCDMA
Mobile Systems Päivämäärä: 13.11.2001 Sivumäärä: 66
Osasto: Teknillisen fysiikan ja matematiikan osasto
Professuuri: Mat-2 Sovellettu matematiikka
Työn valvoja: Professori Raimo P. Hämäläinen
Työn ohjaaja: Dipl.ins. Albert Höglund
Tiivistelmä:
Interferenssillä on suuri merkitys DS-CDMA tyyppisten mobiiliverkkojen toimintaan. Esimerkki tällaisesta verkosta on kolmannen sukupolven matkapuhelinverkko UMTS. Korkea interferenssi pienentää solun kokoa, ja lisää todennäköisyyttä sille, että hyvää yhteyttä mobiilin päätelaiteen ja tukiaseman välillä ei kyetä ylläpitämään. Interferenssin määrä systeemissä lisääntyy verkkoon hyväksytyn käyttäjämäärän kasvaessa. Tämä tarkoittaa sitä, että kapasiteetin kasvattaminen tapahtuu laadun heikkenemisen ja peittoalueen pienenemisen kustannuksella. Vastaavasti laadun parantaminen ja peittoalueen kasvattaminen pienentää systeemin kapasiteettia.
Systeemin kuormaa kontrolloidaan radioresurssien hallinnalla (RRM). RRM:n optimoinnilla ja automatisoinnilla on tärkeä merkitys sekä operaattoreille että laitevalmistajille, koska RRM:llä on suuri vaikutus mobiilin järjestelmän stabiiliudelle ja suorituskyvylle.
Tässä työssä tarkastellaan nousevan siirtotien (suunta mobiilista päätelaitteesta tukiasemaan) pääsynvalvontaa, ja siihen kiinteästi liittyviä alueita kuten CDMA:ta ja RRM:ää. Pääpaino työssä on interferenssiperustaisella pääsynvalvonnalla, ja erityisesti tutkitaan mahdollisuutta parantaa systeemin laadullista suorituskykyä säätämällä raja-arvoa, joka rajoittaa maksimaalista vastaanotettavaa kokonaistehoa nousevalla siirtotiellä.
Ehdotetun algortimin vaikutusta järjestelmän suorituskykyyn tutkitaan simuloimalla sekä piirikytkentäistä reaaliaikaista puheliikennettä että interaktiivista pakettiliikennettä. Laatuindikaattoreina käytetään puhelun estotodennäköisyyttä, huonon puhelun esiintymistodennäköisyyttä ja menetetyn puhelun todennäköisyyttä. Nämä tekijät yhdistetään kustannusfunktiolla, jolla voidaan arvioida koko järjestelmän laadullista suorituskykyä.
Simulointien tulokset tukevat oletusta, että järjestelmän nousevan siirtotien suorituskykyä voidaan parantaa ehdotetulla dynaamisella algoritmilla.
Avainsanat: WCDMA, interferenssi, UMTS, radioresurssien hallinta,
pääsynvalvonta, palvelunlaatu
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Acknowledgements
This Master's thesis is made in Nokia Research Center. Special thanks are due to senior
research engineer Albert Höglund for the guidance of this work. I also wish thank research
manager Olli Karonen and senior research engineer Petri Niska for providing the opportunity
to finish this work. I am grateful for Professor Raimo P. Hämäläinen for supervising this
thesis.
Espoo, 13th November 2001,
Janne Pöllönen
ii
Contents
1 INTRODUCTION....................................................................................................................... 1
2 UMTS........................................................................................................................................... 3
2.1 STANDARDIZATION ................................................................................................................... 3
2.2 QOS CLASSES ........................................................................................................................... 3
2.3 CELL TYPES .............................................................................................................................. 5
2.4 NETWORK ARCHITECTURE........................................................................................................ 6
2.4.1 UMTS Radio Access Network ......................................................................................... 7
2.4.2 Core Network.................................................................................................................. 8
3 WCDMA RADIO ACCESS ....................................................................................................... 9
3.1 MULTIPLE ACCESS.................................................................................................................... 9
3.2 CDMA PRINCIPLES................................................................................................................. 10
3.3 DIRECT SEQUENCE CDMA...................................................................................................... 14
4 RADIO RESOURCE MANAGEMENT ................................................................................. 19
4.1 POWER CONTROL.................................................................................................................... 19
4.2 HANDOVER CONTROL............................................................................................................. 20
4.3 PACKET SCHEDULER............................................................................................................... 20
4.4 LOAD CONTROL...................................................................................................................... 21
5 UPLINK ADMISSION CONTROL AND QUALITY OF SERVICE.................................. 22
5.1 UPLINK CAPACITY AND COVERAGE ......................................................................................... 22
5.2 CALL ADMISSION STRATEGIES................................................................................................ 26
5.3 INTERFERENCE BASED ADMISSION CONTROL STRATEGY ......................................................... 28
5.4 QUALITY OF SERVICE IN INTERFERENCE-BASED ADMISSION CONTROL.................................. 31
6 SIMULATIONS ........................................................................................................................ 36
6.1 SIMULATION SETUP ................................................................................................................ 36
6.2 RESULTS ................................................................................................................................. 40
6.2.1 Scenario 1: Speech ....................................................................................................... 40
6.2.2 Scenario 2: Mixed Case................................................................................................ 46
7 CONCLUSIONS ....................................................................................................................... 49
iii
REFERENCES ................................................................................................................................... 51
APPENDICES: ................................................................................................................................... 56
A. ABBREVIATIONS ..................................................................................................................... 56
B. SIMULATION PARAMETERS ..................................................................................................... 59
1
1 Introduction The third generation (3G) mobile telecommunication systems are being deployed and
expected to be running globally very soon. The next generation mobile systems are
designed to enhance the wireless communications in many ways. 3G technologies
provide wideband radio with high spectral efficiency and support for multimedia, circuit
and packet switched traffic. 3G offers greater capacity, higher data rates and a wider mix
of communications services compared to the existing second generation systems. The
new wideband characteristics and the flexibility to introduce new services are to be
exploited by a variety of mobile devices and innovative seamless applications. Examples
of the proposed services include multimedia applications such as mobile video
conferencing and web browsing. Nevertheless, there will probably not be any single
application that is going to dominate the next generation market, and it is rather supposed
that 3G will breed success through its flexibility and a wide range of personal services.
Wideband code division multiple access (WCDMA) has emerged as the mainstream air
interface solution for the next generation networks. It was also selected as the radio
transmission technology (RTT) for UMTS (Universal Mobile Telecommunications
System), which is the European third generation mobile communications system
developed by ETSI (European Telecommunications Standards Institute).
The most essential elements of the third generation mobile systems have already been
standardized, and the basic operational requirements and the system architecture are
already well understood. However, there is plenty of room for innovations and
enhancements in many areas within 3G. For instance, the optimization and autotuning of
the radio resource management (RRM) can significantly increase the operability and the
performance of a mobile network.
In this thesis, admission control (AC) for WCDMA mobile networks is studied.
Admission control is part of radio resource management, and more specifically, it is a
radio access network (RAN) located algorithm or a set of algorithms that determine
whether a new radio access bearer (RAB) can be established.
An effective admission control should ensure that the radio access system operates at a
point, where the radio air interface is fully utilized and the quality of service (QoS) for the
2
ongoing calls is guaranteed. The optimization of admission control in WCDMA networks
is more challenging compared to the second generation systems, because 3G will support
many different QoS classes, and WCDMA capacity and coverage are not fixed, as all the
WCDMA users share the same wideband spectrum at the same time. In this thesis, a
quality of service based way to improve an interference limited uplink admission control
is proposed. The effect of the proposed algorithm is evaluated by system simulations.
The radio resource management, which the admission control is an essential part of, has a
major role in the utilization of air interface resources. Its function is to maximize the
capacity, while providing quality of service and maintaining the stability of the network.
Thus, the optimization of radio resource management and admission control is of high
importance both for the manufacturers and for the operators.
The scope of this thesis is limited to the uplink direction. Uplink, that is, reverse link is
the communication link from a mobile terminal to a base station. The division between
uplink and downlink, that is, forward link is made, since their implementation and
performance are vastly different from each other, and radio resource management
operates largely independently in both directions. This study also assumes that frequency
division duplex (FDD) mode, in which the paired carriers with equal bandwidths are
allocated for the uplink and downlink, is used for the communication.
The thesis is organized using the top-down approach. First, a general introduction to
UMTS is presented in chapter 2. Then, chapter 3 gives a presentation of the WCDMA
principles. The radio resource management is studied in chapter 4. The RRM described is
general enough to illustrate the basic mechanisms behind the utilization and managing of
the WCDMA based air interface resources. Together, WCDMA and RRM form the basic
underlying concepts for the optimization of admission control. The focus of RRM, in this
thesis, is the uplink admission control, which is covered in detail in chapter 5. In the same
chapter, an improved quality of service based uplink admission control strategy is
proposed. The performance of the proposed algorithm is investigated with simulations
using a dynamic system simulator in chapter 6. Finally, the conclusions are presented in
chapter 7.
3
2 UMTS UMTS (Universal Mobile Telecommunications System) is one of the major new third
generation mobile communications systems being developed within the framework,
which has been defined by ITU (International Telecommunications Union) and known as
IMT-2000 (International Mobile Telephony). UMTS facilitates convergence between
telecommunications, IT, media and content industries. It has potential to provide end
users with data rates up to 2 Mbps, and it lends itself to give individuals the freedom to
choose among a wide range of services currently in existence or soon to exist. Some
examples of the new services are video telephony and quick access to information and
fast download of data, for instance, on Internet directly for people on the move.
2.1 Standardization International Telecommunications Union is coordinating 3G standardization. Within ITU,
the third generation systems are called International Mobile Telephony 2000. Regional
standardization organizations, such as ETSI in Europe, have specified their proposals to
fulfill the IMT-2000 requirements. The third generation system is called UMTS within
ETSI.
In the standardization forums, wideband CDMA has emerged as the most widely adopted
third generation air interface[1]. In addition, ETSI selected WCDMA as the basic access
scheme in January 1998. WCDMA specification is produced in 3GPP (Third Generation
Partnership Project)[2], which is the joint standardization project of the standardization
bodies from Europe, Japan, Korea, the USA and China.
To date, 13th of November 2001, UMTS licenses have been awarded in more than fifteen
countries, and experimental systems are made with field trials and commercial services
are being launched in Japan and on the British Isle of Man[3]. The standards bodies and
industrial interest groups mentioned above can be found in [4-7].
2.2 QoS Classes UMTS has been designed to support a variety of quality of service (QoS) requirements
that are set by end users and end-user applications. The third generation services will vary
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from simple voice telephony to more complex data applications including voice over IP
(VoIP), video conferencing over IP (VCoIP), web browsing, email and file transfer.
3GPP has identified four different main traffic classes for UMTS according to the nature
of traffic: conversational class, streaming class, interactive class and background class[8].
The best-known use of conversational class is telephony speech. With Internet and
multimedia, a number of new applications, for example, VoIP and video conferencing
tools will require this scheme. Real time conversation is always performed between peers
of human end users. This is the only traffic type where the required characteristics are
strictly imposed by human perception. Real time conversation is characterized by the fact
that the transfer time and time variation between information entities must be low and
preserved.
Streaming class is applied when the transferred data is processed as a steady and
continuous stream. Accordingly, the streaming class is characterized by the preserved
time variation between information entities of the stream, but it does not have any
requirements on low transfer delay. Thus, the acceptable delay variation over
transmission media, that is, jitter is much higher than in the conversational class. An
example of this scheme is the user looking at real-time video or listening to real-time
audio.
When the end user, either a machine or human, is on-line requesting data from remote
equipment (e.g., a server), interactive class scheme applies. Examples of interactive
human interaction with remote equipment are web browsing, database retrieval and server
access. Examples of machine interaction with remote equipment are polling for
measurement records and automatic database enquiries. Interactive class is characterized
by request response pattern (round trip delay and response time) and preserved payload
content (low bit error rate).
Applications such as email and SMS, download of databases and reception of
measurement records generate distinctive background class traffic. Background traffic
scheme is characterized by the fact that the destination is not expecting the data within a
certain time, but that the data integrity must be preserved during the delivery. The UMTS
QoS classes are summarized in Table 2-1.
5
Table 2-1 UMTS QoS classes.
Traffic class Conversational
class
Streaming class Interactive class
Background class
Fundamental characteristics
• Preserve time relation (variation) between information entities of the stream
• Conversational pattern (stringent and low delay)
• Preserve time relation (variation) between information entities of the stream
• Request response pattern
• Preserve payload content
• Destination is not expecting the data within a certain time
• Preserve payload content
Example of the application
− Voice
− Video telephony
− Video games
− Streaming multimedia
− Web browsing
− Network games
− Background download of emails
The requirements of the QoS classes are met by negotiating appropriate QoS attribute
values for each established or modified UMTS bearer. Traffic parameter set consists of
eight different attributes: Maximum bit rate (kbps), guaranteed bit rate (kbps), delivery
order (yes/no), SDU (Service data unit) size information (bits), reliability, transfer delay
(s), traffic handling priority and allocation/retention policy[8].
2.3 Cell Types For an optimal UMTS performance, it is proposed that UMTS network is planned with a
hierarchical cell structure (HCS) using macro, micro and pico cells[9-11]. In general, the
more stringent the QoS and capacity requirements, the smaller the cell needs to be. A
possible use of the hierarchical cell structure is shown in Figure 2-1. Large cells
guarantee a continuous coverage for fast moving mobiles, while small cells are necessary
to achieve good spectrum efficiency and high capacity for hot spot areas. With flexible
deployment, it could be possible for an operator to redeploy pico cell channels for macro
cells outside of urban cells in some locations.
6
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Figure 2-1 UMTS hierarchical cell scenario (redrawn from [7]).
The FDD macro cellular network provides the wide area coverage and it is used for high-
speed mobiles. The micro cells are used at street level for outdoor coverage to provide
extra capacity where macro cells could not scope. It would seem likely that these micro
cells would not be hexagonal in shape but rather canyonlike, reflecting the topography of
a street and be perhaps 200–400 m in distance. The pico cell would be deployed mainly
indoors in areas where there is a demand for high data rate services such as laptops
networking or multimedia conferencing. Such cells may be of the order of 50 m in
distance. A limiting factor will be the range of these terminals when used for high data
rate services given the high demand this will place on batteries. Maximum bit rate for
macro cells is to be 384 kbps and 2 Mbps for pico cells.
2.4 Network Architecture UMTS network architecture will be an evolution of GSM and GPRS network, thus
resembling very much of their architecture. It consists of two parts: UMTS terrestrial
radio access network (UTRAN) and core network (CN). UTRAN provides the air
7
interface for UMTS terminals and core network is responsible for switching and routing
of calls and data connections to external networks. The UMTS system architecture with
the interfaces is depicted in Figure 2-2. The interfaces are defined open to allow the
equipment at the endpoints to be from two different manufacturers. A complete
description of the network architecture and the interfaces between the logical network
elements can be found in 3GPP technical specifications (TS)[6].
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Figure 2-2 UMTS network architecture.
2.4.1 UMTS Radio Access Network
UTRAN consists of one or more radio network subsystems (RNS). A radio network
subsystem consists of a radio network controller (RNC), several node Bs (UMTS base
stations) and user equipment (UE).
The radio network controller is responsible for the control of radio resources of UTRAN.
It plays a very important role in power control (PC), handover control (HC), admission
control (AC), load control (LC) and packet scheduling (PS) algorithms, which are at least
partially located at RNC. RNC interfaces the core network via Iu interface and uses Iub to
control one node B. The Iur interface between RNCs allows soft handover between
RNCs.
Node B is equivalent to the GSM base station (BS/BTS), and it is the physical unit for
radio transmission and reception with cells. Node B performs the air interface processing,
which includes channel coding, interleaving, rate adaptation and spreading. The
connection with the user equipment is made via Uu interface, which is actually the
8
WCDMA radio interface. Node B is also responsible for softer handovers and inner
closed-loop power control.
User equipment is based on the same principles as the GSM mobile station (MS), and it
consists of two parts: mobile equipment (ME) and the UMTS subscriber identity module
(USIM). Mobile equipment is the device that provides for radio transmission, and the
USIM is the smart card holding the user identity and personal information.
2.4.2 Core Network
UMTS is based on an evolved core GSM network integrating circuit and packet switched
traffic. The entities of CN, shown in Figure 2-2, are home location register (HLR), mobile
services switching center/visitor location register (MSC/VLR), gateway MSC (GMSC),
serving GPRS support node (SGSN) and gateway GPRS support node (GGSN).
The home location register is a database in charge of the management of mobile
subscribers. It holds the subscriber and location information enabling the charging and
routing of calls towards the MSC or SGSN, where the mobile station is registered at that
time.
The mobile switching center constitutes the interface between the radio system and the
fixed networks. The MSC performs all necessary functions in order to handle the circuit
switched services to and from the mobile stations. A mobile station roaming in an MSC
area is controlled by the visitor location register in charge of this area.
Gateway MSC is the switch at the point where UMTS public land mobile network
(PLMN) is connected to external circuit switched networks. All incoming and outgoing
circuit switched connections go through GMSC.
Serving GPRS support node has similar functionality to that of MSC/VLR, but it is used
for packet switched services. Gateway GPRS support node has the same functionality for
the packet domain as the GMSC has for the circuit domain.
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3 WCDMA radio access
3.1 Multiple Access The basis for any mobile system is its air interface design, and particularly the way the
common transmission medium is shared between users, that is, multiple access
scheme[12]. Multiple access scheme defines how the radio spectrum is divided into
channels, and how the channels separate the different users of the system. WCDMA is the
multiple access method selected by ETSI as basis for UMTS air interface technology.
Multiple access schemes can be classified into groups according to the nature of the
protocol[13]. The basic branches are contentionless (scheduling) and contention (random
access) protocols.
The contentionless protocols avoid the situation in which two or more users access the
channel at the same time by scheduling the transmissions of the users. This can be done
in a fixed fashion by allocating each user a static part of the transmission capacity, or in a
demand-assigned fashion, in which scheduling only takes place between the users that
have something to transmit.
The fixed-assignment technique is used in frequency division multiple access (FDMA)
and time division multiple access (TDMA), which are combined in many contemporary
mobile radio systems such as GSM[14]. In a FDMA system, the total system bandwidth
is divided into several frequency channels that are allocated to users. In a TDMA system,
one frequency channel is divided into time slots that are allocated to users, and the users
only transmit during their assigned timeslots. Examples of demand-assignment
contentionless protocols are token bus and token ring LANs described by the IEEE in the
802.4 and 802.5 standards[15].
With the contention protocols, a user cannot be certain that the transmission will not
collide, since other users may be accessing the channel at the same time. If several users
transmit simultaneously, all of their transmissions will fail. Contention protocols, for
example ALOHA-type protocols[16], resolve conflicts by waiting a random amount of
time until retransmitting the collided message.
10
CDMA, and thus WCDMA, is very different from the techniques explained above. In
principle, it is a contentionless protocol allowing a number of users to transmit at the
same time without conflict. However, contention will occur if the number of
simultaneously transmitting users rise above some threshold.
In CDMA, each user is assigned a distinct code sequence (spreading code) that is used to
encode the user's information-bearing signal. The receiver retrieves the desired signal by
using the same code sequence at the reception. The division of TDMA, FDMA and
CDMA channels into time-frequency plane is illustrated in Figure 3-1.
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Figure 3-1 Multiple access schemes: (a) FDMA (b) TDMA (c) CDMA
3.2 CDMA principles Spread spectrum techniques use transmission bandwidth that is many times greater than
the information bandwidth of any user. All radio resources are allocated to all users
simultaneously. In CDMA, all communicating units transmit at the same time and over
the same frequency. Multiple access is achieved by assigning each user or channel a
distinguished spreading code (chip code). This chip code is used to transform a user’s
narrowband signal to a much wider spectrum prior to transmission. The receiver
correlates the received composite signal with the same chip code to recover the original
information-bearing signal.
The ratio of the transmitted bandwidth Bt to information bandwidth Bi is an important
concept in CDMA systems. It is called the processing gain or the spreading factor, Gp, of
the spread spectrum system (Eq. 3-1). The capacity of the system and its ability to reject
interference are directly proportional to Gp. Wide CDMA bandwidth, that is, high chip
code rate gives higher processing gains, and thus better system performance.
11
i
tp B
BG = (Eq. 3-1)
When multiple users transmit a spread spectrum signal at the same time, the receiver is
able to distinguish the information signal, since each user's distinct code has good auto-
and cross-correlation properties. Thus, as the receiver decodes (despreads) the received
signal, the transmitted signal power is increased above the noise, while the signals of the
other users remain spread across the total bandwidth. The principle of the spreading and
despreading is illustrated in Figure 3-2. In Figure 3-2a, the data signal of user 1 is spread
into wideband signal. Figure 3-2c shows the spreading operation for several other users.
Figure 3-2b illustrates the received wideband signal, which consists of the signals from
all the users, inclusive user 1. Figure 3-2d shows the signal powers after the despreading
operation with the code of user 1. The signal of user 1 is retrieved by the receiver,
whereas the rest of the signals appear random and are experienced as noise.
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Figure 3-2 Principle of spread spectrum access: (a) User 1 signal spreading (b) The received signal (c) Spreading for several users (d) Despread signal for user 1.
The described multiple access fully distinguishes CDMA from other multiple access
systems. This makes the radio resource management of CDMA very challenging, since
there is no absolute upper limit on the number of users that can be supported in each cell.
This feature of CDMA is also called soft capacity. If the users are allowed to enter the
12
system without any restrictions, the interference may increase to intolerable levels, thus
damaging the quality of reverse links by causing power outage of some terminals.
This thesis tries to find an efficient way to limit the number of uplink calls in order to
improve the performance of the system. In general, the maximum number of users
depends on many factors. These include interference that is generated at the base station
by all the uplinked signals from own cell and other cells, and the propagation conditions
which consist of path loss, shadowing and fast-fading. As already indicated, the
components of the total interference are cross-correlation interference of users' signals
and background noise. Overall, the CDMA systems are interference limited. The
interference concept is essential for this thesis from admission control point of view and
admission control related interference issues will be dealt separately in chapter 5.
As described above, CDMA systems have limitations due to interference, and a brief
summary is given next of the elements and technical solutions that are fundamental for
the performance of a real CDMA network.
• Power control (PC) – Combats near-far problem. That is a situation, in which a
mobile device close to a base station is received at higher power than a mobile
located further away. Consequently, the reception of the mobile device's
transmission is blocked. Power control solves this by increasing the output
power as the mobile moves away from the base station, and by decreasing the
transmit power as the mobile moves closer to the base station. Power control
measures the signal-to-interference ratio (SIR) and sends commands to the
transmitter on the other end to adjust the transmission power accordingly.
Power control is used in both directions in WCDMA.
• Soft handover – Handover (handoff) is the action of switching a call in
progress from one cell to another without interruption when a mobile station
moves from one cell to another. Neighboring cells in FDMA and TDMA
cellular systems do not use the same frequencies. In those systems, a mobile
station performs a hard handover when the signal strength of a neighboring cell
exceeds the signal strength of the current cell with some threshold. In CDMA
systems, the universal frequency reuse with factor of one is used. Thus, the
previous approach would cause excessive interference in the neighboring cells.
13
Neither is it feasible to perform an instantaneous handover, which would
naturally solve this problem. The solution in CDMA systems is soft handover
(soft handoff), in which a mobile user may receive and send the same call
simultaneously from and to two or more base stations. In this way, the
transmission power of a mobile can be controlled by the prevailing base station
that receives the strongest signal.
• Multipath signal reception - In a multi-path channel, the original transmitted
signal reflects from obstacles such as buildings and mountains, and several
copies of the signal, with slightly different delays, arrive at the receiver. From
each multi-path signal's point of view, other multi-path signals can be regarded
as interference and they are suppressed by the processing gain like other signals
using the same channel. However, CDMA uses the Rake technique, in which
the receiver has several parallel correlators that process the multipath
components independently, and align them for optimal combining.
Wideband CDMA is an extension of CDMA architecture using a large bandwidth of at
least 5 MHz, and it has more advanced characteristics than the second generation CDMA
systems. WCDMA is characterized by the following items:
• High chip rate (3.84 Mcps) and data rates (up to 2 Mbps)
• Provision of multirate services
• Packet data
• Fast power control in the downlink
• Asynchronous base stations
• Seamless interfrequency handover
• Intersystem handovers, e.g., between GSM and WCDMA
• Support for advanced technologies like multi-user detection (MUD)[17] and
smart adaptive antennas
There are two major techniques for obtaining a spread-spectrum signal: frequency
hopping (FH) and direct sequence (DS) spreading[18]. They are briefly reviewed in the
following:
14
• Direct sequence spread spectrum (DS-SS). The data is directly coded by a high
chip rate (spreading) code by multiplying the information-bearing signal with a
pseudorandom ± binary waveform. The receiver knows how to generate the
same code, and correlates the received signal with that code to extract the
original data. UMTS is based on DS-CDMA. The important principles of DS-
CDMA will be discussed in chapter 3.3.
• Frequency hopping spread spectrum (FH-SS). The carrier frequency at which
the data is transmitted is changed rapidly according to the spreading code. By
using the same code, the receiver knows where to find the signal at any given
time.
3.3 Direct sequence CDMA Direct sequence CDMA (DS-CDMA) has been described widely in the literature, for
instance, in [13] and [18-20]. In DS-CDMA the original information-bearing signal, that
is, data signal is modulated on a carrier, which is spread by a high rate binary code
sequence (chip code) to produce a bandwidth much larger than the original bandwidth.
Logical binary symbols, bits 0 and 1, are suggested to be considered as mapped to real
values –1 and +1 during the spreading operation. Various modulation techniques can be
used for the code modulation, but usually some form of phase shift keying (PSK) such as
binary phase shift keying (BPSK), quadrature phase shift keying (QPSK) or minimum
phase shift keying (MSK) is employed.
The modulated wideband signal is transmitted through the radio channel. During the
transmission, the modulated signal suffers from interference caused by the signals of
other users. The desired signal together with interference reaches the receiver. At the
reception, the receiver correlates the composite signal with the chip code of the desired
signal. The multiplication by the distinct ± binary spreading waveform filters out large
part of interference, and the original data is recovered. The cross-correlations of the code
sequences of different users should be small so that the power ratio of the desired signal
to the interfering signals will be large. The discrete cross-correlation between two
different codes is given by:
15
∑
=+=
N
nknnba
NkR
1
1)( (Eq. 3-2)
where an and bn are the elements of the two sequences with code period N, and k is the
time lag between the signals.
In the following, the use of DS-CDMA will be illustrated by examples using the simplest
form of spreading modulation, that is, BPSK. In BPSK modulation, the phase of the
carrier is shifted 180 degrees in accordance with the transmitted digital bit stream. In the
examples, a single bit transition, from 1 to 0 or from 0 to 1, causes a phase shift whereas
two successive bits with equal values do not result in a phase shift. Let x(t) be the data
stream that is to be modulated by a carrier having power P and radian frequency ω0.
Then, the modulated stream, sd(t), can be defined as:
)sin()(2)( 0ttxPtsd ω⋅= (Eq. 3-3)
where x(t) = ± 1.
As an example, let the data stream being modulated to be (1 0) as in Figure 3-3a. The
BPSK modulated data signal, sd(t), is shown in Figure 3-3d. The wideband BPSK
spreading is accomplished by multiplying sd(t) by a function c(t) that takes on values ±1.
The transmitted wideband signal, st(t), can thus be represented by:
)sin()()(2)( 0ttxtcPtst ω⋅= (Eq. 3-4)
Let the chip code sequence c(t) to be (1 0 1 0), with processing gain four, as shown in
Figure 3-3b. When modulo-2 addition is used, the spread data will be as shown in Figure
3-3c. The resulting transmission wave is depicted in Figure 3-3e. As previously noted, the
signal will be despread at the receiving end using the same code as in transmission. After
demodulation and despreading, the original data will be recovered.
16
The received signal has a propagation delay Td that is determined by the path length. The
signal, st'(t), coming out of the receivers correlator is:
[ ])(sin)(2 0''
ddddt TtωTt)xT)c(tTc(tP(t)s −−−−⋅= (Eq. 3-5)
where T'd is the receiver’s best estimate of the transmission delay. It can be seen that if
the chip code c(t) at the receiver is correctly synchronized with the chip code at the
transmitter (i.e., T'd = Td), the original data is recovered after despreading and
demodulation.
00.5
1
00.5
1
00.5
1
-101
-10
1
1 0
1 0 1 0 1 0 1 0
1 0 1 0 0 1 0 1
(a)
(b)
(c)
(d)
(e)
Figure 3-3 (a) User data (b) Spreading sequence (c) Spread data (d) Modulated data signal (e) Transmitted signal.
As a second example, the spreading and despreading is illustrated with three users. Let
the data and the chip sequence of user 1, which are shown in Figure 3-4a, be the same as
those used in Figure 3-3a and Figure 3-3b. Let the data of user 2 be (1 0) and the
spreading code (1 0 0 1). They are shown in Figure 3-4c. In addition, let the data stream
of user 3 to be (0 0) and the spreading code (1 1 0 0), as shown in Figure 3-4e. The
selected processing gain is again 4. Figure 3-4b, Figure 3-4d and Figure 3-4f illustrate the
17
spread signals of users 1, 2 and 3, respectively. The resulting composite signal of all the
users is given by Figure 3-4g. Figure 3-4h shows the effect of the despreading operation
when the despreading is applied to user 1. The decoded chips are integrated to give the
decoded data. The retrieved signal is the original one, since the multiplication of the
composite signal by the user 1 chip code cancels the interfering codes from others users.
This is because the cross-correlation, R(k) (Eq. 3-2), between the chip codes is zero, as
the codes were selected orthogonal in the example.
00.5
1
00.5
1
00.5
1
00.5
1
00.5
1
00.5
1
-1.50
1.53
-202
solid line is data
decoded chip
dashed line is chip code
transmitted code
user 2
user 3
composite code user 1 chip code
(h) decoded data
(b)
(g)
(f)
(c)
(d)
(e)
(a) user 1
Figure 3-4 (a) User 1 data and the spreading sequence (b) Encoded user 1 data (c) User 2 data and the spreading sequence (d) Encoded user 2 data (e) User 3 data and the spreading sequence (f) Encoded user 3 data (g) Composite data and spreading sequence for user 1 (h) Decoded chip and data for user 1.
It should be noted that orthogonal codes are completely orthogonal only for zero delay.
For other delays, orthogonal codes have poor cross-correlation properties. Thus, they are
suitable only if all the users of the same channel are synchronized in time to the accuracy
of a small fraction of one chip. This is why PN (pseudo noise) codes are necessary in the
18
reverse link. WCDMA uses Gold-sequences, which is a class of PN-code, for cell and
user separation both in the downlink and in the uplink, and orthogonal codes for channel
separation[21]. The performance and interference resistance properties of Gold and other
scrambling codes are evaluated in [22]. The choice of the spreading code is very
important, as it is the basic building block of any CDMA system. Many families of
spreading codes, with satisfactory auto- and cross-correlation properties, exist[18], [19],
[23].
In the actual systems, the processing gain is usually much larger than four, the value that
was used in the previous examples. A large processing gain is, of course, highly
beneficial in suppressing interference. For instance, the chip rate of WCDMA is 3.84
Mcps, which allows large spreading.
19
4 Radio Resource Management Radio resource management (RRM) is a set of algorithms that control the usage of
WCDMA radio resources. It is located in user equipment, base station and radio network
controller inside UTRAN. In the second-generation networks, RRM is based on hard
limits, which means that a fixed number of channels are allocated to the users. Soft
capacity and flexible services make the RRM of the third generation systems more
complex than it is in the second-generation systems. The RRM infrastructure presented in
this chapter is based on [24].
RRM functionality is aimed to guarantee quality of service, to offer high capacity and to
maintain the planned coverage area. Thus, RRM optimization and autotuning are an
important part of WCDMA systems when trying to achieve efficient performance of the
radio access network. The basic RRM can be classified into the following modules:
power control (PC), handover control (HC), admission control (AC), packet scheduling
(PS) and load control (LC). The interference-based admission control, which is the focus
of this thesis, is studied in chapter 5. In this chapter, a short overview of the other RRM
functionalities is given to illustrate the relation of admission control to other RRM
algorithms.
4.1 Power Control Power control (PC) provides protection against shadowing, fast-fading and near-far
problem (described in chapter 5.1 and 3.2), all of which cause variation in the received
signal strength. The protection is given by controlling the power of the users to be the
minimum required to maintain a given signal-to-noise ratio (SIR) for the required level of
performance. In this way, each user contributes to the interference to the least extent
possible. Power control is employed on a connection basis. Typically, a slow outer-loop
power control and a fast closed-loop power control are used[25]. Without an accurate
power control, WCDMA systems cannot operate.
Fast power control compensates for the rapid signal fluctuation at the receiver. The
receiver estimates the received SIR, and sends a power control command (TPC) to the
20
other end to either increase or decrease its transmission power. The frequency of fast
power control in WCDMA is 1.5 kHz in both uplink and downlink.
Because the same SIRs correspond to different frame error rates (FERs) in different radio
environments and conditions, outer-loop power control is needed to map the desired FER
into the required SIR target. The SIR-target is independently adjusted for each connection
based on the FER measurements during the connection. The frequency of the outer loop
power control is typically 10–100 Hz.
4.2 Handover Control Handover (handoff) means the action of switching a call in progress between radio
channels in the same cell or switching a call from one cell to another without interruption
of the call. It is essential to guarantee the mobility of a subscriber. Handover in WCDMA
is described in [26]. In WCDMA, handovers can generally be divided into soft handovers
and hard handovers.
Soft handover (SHO) is a necessary element of CDMA systems to avoid excessive
interference from the neighboring cells, as described in chapter 3.2. In soft handover, a
mobile station is simultaneously connected to more than one base station. SHO increases
the performance by diversity, but at cost of a greater number of connections. When the
signal strength of a base station pilot exceeds the add threshold, the mobile station enters
the soft handover state. When the signal strength drops below drop threshold, the base
station is removed from the set of cells that form a soft handover.
Hard handovers in WCDMA refer, for instance, to inter-frequency and inter-system
handovers. Inter-frequency handovers are used to balance the load between the carriers if
a base station uses several of them. Inter-system handovers can be made for quality or
coverage reasons, for instance, between WCDMA and GSM.
4.3 Packet Scheduler The task of packet scheduler (PS) is to support packet switched mode at the radio
interface. Its function is to divide the available air interface capacity between the packet
21
data users, decide the transport channel for each user's packet data transmission, and to
monitor the packet allocation and the system load[24].
The capacity division means the way the packet scheduler allocates bit rates for bearers
and how it modifies them during the connections. Packet scheduler can select different
transport channels for different type of packet data. Common channels are used for small
packet transmissions, dedicated channels for high bit rate sessions and shared channels
for low bit rate sessions.
4.4 Load Control The task of load control (LC) is to ensure that the system remains stable and does not
become overloaded. Thus, the basic purpose of load control is the same as that of
admission control. The main conceptual difference is that load control is a continuous
process, whereas admission control is carried out as a single event.
Load control performs its task by measuring the amount of uplink interference and the
total downlink transmission power. If an overload situation is encountered, load control
returns the system quickly and controllably back to the normal state (load). The load
control performs both preventive actions, for instance, reduction of Eb/N0 targets, and, in
rare cases, overload control actions such as dropping of connections.
22
5 Uplink Admission Control and Quality of Service
5.1 Uplink capacity and coverage Capacity and coverage are the most important aspects in network planning. The coverage
of a base station sector for a given service is the geographical area where a mobile unit is
able to communicate with the base station with the required signal level. The capacity of
the cell is defined by the number of connections that can simultaneously exist with an
acceptable level of mutual interference.
WCDMA's uplink soft capacity is limited by the amount of interference, caused by
mobile units, that can be tolerated in a given cell to overcome path loss, shadowing and
fast-fading. Path loss is the distance attenuation of signal strength between the receiver
and transmitter antennas. Shadowing refers to slow variations in propagation due to
changes in large-scale terrain characteristics caused, for instance, by trees and foliage.
Fast-fading means the fluctuation of the received signal envelope over short distance and
time as a result of multi path reflections of the transmitted signal from local objects such
as buildings.
Interference on the reverse links consists of the superposition of the signals from mobile
units at the base station receiver. The interference curve, as a function of the number of
connections, is likely to exhibit a steepening form, because more load requires more
power from the all existing connections, which adds more load. To reduce interference,
power control attempts to minimize all users' received signal powers at the base station,
while maintaining satisfactory link performance. Soft handover guarantees that the user is
connected at all times to the best base station, that is, the one with the least attenuation
due to propagation losses.
Interference originates mainly from the same cell users, but much interference arrives at
the given base station also from the users controlled by the base stations of other cells. In
addition, there is always system noise, for instance, the environmental (thermal) and
manmade background noise. As already indicated, the other cell interference is also
received at the given base station with the lowest possible power levels, since soft
23
handover guarantees that the user is connected at all times through the best base station.
Other cell interference decreases rapidly as the mobile unit moves away from the
boundary of cells because path loss increases exponentially. Path loss is generally
modeled to have the functional form x-α, where x is the distance and α is path loss
exponent, which is reported to have values ranging from 3.0 to 5.0 depending on the
environment[17]. Other cell interference has been estimated from 33 % to 42 % of the
total power received from mobiles in the same cell, and consequently CDMA capacity
under a multicell environment equaling to 70 to 75 % of the capacity under a single cell
environment[18]. The effect of other cell interference to the capacity can be seen in the
simplified formula for the reverse link capacity (Eq. 5-2), which is to be derived next.
In the following theoretical calculation of uplink capacity, identical users and perfect
power control are assumed. Suppose that the demodulator for each user can operate
against Gaussian noise at a bit-energy-to-noise-density level of Eb/I0.1 The received
energy per bit is the ratio between the received signal power, Ps, to the data rate, which is
the entire spread-spectrum bandwidth rate per processing gain (Eq. 5-1a). The noise
density, I0, is given in (Eq. 5-1b) where Iown' denotes own-cell interference, Iother other-cell
interference and N0 background noise. The fraction of intra-cell interference of the total
interference, F, is given by (Eq. 5-1c). The expressions for the own-cell interferences are
obtained by (Eq. 5-1d) and (Eq. 5-1e), where N is the number of users. It should be noted
that expression (Eq. 5-1e) includes the observed user's reception power, whereas (Eq. 5-
1d) does not.
1 A common convention is to use notation Eb/N0 to represent bit-energy-to-noise-density, but here,
in this context, the symbol I0 is employed to denote the whole noise density, and N0 includes only
the thermal background noise.
24
( )( )
⋅=⋅−=
+=
++=⋅=
sown
sown
otherown
own
otherown
psb
PNIPNI
IIIF
WNIIIWGPE
(e))1( (d)
(c)
/ (b)/ (a)
'
00 '
(Eq. 5-1)
If the background noise N0 is neglected, the above set of equations yield the capacity
expression:
+⋅= 1
0IEG
FNb
p (Eq. 5-2)
Similar capacity calculations can be found in [27] and [28]. The Eb/I0 requirement of a
user depends on the bit rate, bearer service, multipath profile, mobile speed, receiver
algorithms and base station antenna structure.
The interference-based uplink capacity and coverage is determined by the base station
receiver sensitivity and the amount of power transmitted by the mobile unit. The power
outage occurs when the mobile maximum power is not enough to meet the required
signal-to-interference level due to large path loss and shadowing. In general, the power
outage probability increases near the edge of the cell. Moreover, the outage probability
and capacity of CDMA has been found to be very sensitive to the imperfections of the
power control[29-30]. The WCDMA reduces the impact of imperfect power control
through better diversity.
The coverage and capacity are inter-related through interference. As the number of users
in a cell grows, the interference levels at the base station receiver increase, as well. This
means that far-away users cannot maintain the link quality to that base station, and they
will be served by adjacent cells. Hence, the increased load actually causes the cell to
shrink. Conversely, the smaller the interference, and thus the capacity, the greater the
coverage. The feature that traffic intensity affects the cell size is known as cell breathing.
Accordingly, there will always be an inherent trade-off between coverage and capacity in
25
CDMA. In exactly the same way, there will also be a trade-off between capacity and
quality of service.
Uplink and downlink are not operated in an identical condition, and their performance
characteristics are vastly different. Both directions are ultimately limited by interference,
but there are large dissimilarities, since the forward link access is of one-to-many type
and the reverse link is of many-to-one type. It is apparent that the forward link is limited
by the total base station transmission power and the power limit per radio link, while the
reverse link is limited by individual mobile transmission powers. In this thesis, the uplink
direction is examined. It is not studied closely which link limits the system capacity and
coverage in a particular WCDMA system, but some general attention needs to be paid to
the unbalance of UL and DL, though.
Either of the two links, UL or DL, can determine the whole system capacity. It is
generally difficult to draw a firm conclusion, which of the links limits the system capacity
and coverage, and what are the limiting factors[31]. The limiting link is determined, for
instance, by other-cell interference, multipath fading, effectiveness of power control,
spatial distribution of users, and generation, synchronization, modulation and coding of
the spread-spectrum signal. The overall capacity of narrowband CDMA systems, where
the main service has traditionally been the voice communications, is often argued to be
uplink limited in the literature[30-32]. WCDMA and 3G mobile communications with
multimedia services may well change that stance.
An uplink limited system capacity in WCDMA is more likely to occur in a rural
environment, where far-away mobile units cannot transmit with the required power.
Dense urban areas are more likely to have the downlink limited capacity, since the base
station could run out of transmit power before the terminals, because the total BS power
is shared between all the users[24], [33]. Uplink and downlink capacity relationship has
been concluded to be highly dependent on the network configuration such as base station
locations[34]. The coverage of WCDMA is assumed uplink limited in high load case
[24], [33].
It is important to remember that in third generation cellular systems the traffic and load
can be asymmetric between uplink and downlink. Some applications such as www-
browsing or electronic newspaper download cause the capacity utilization to be strongly
26
biased toward downlink. It was concluded in [34], that a small amount of www-browsing
traffic turned the downlink direction as the capacity limiting factor of the WCDMA
network. In addition, [31] suggests that WCDMA capacity is generally downlink limited.
There will also exist link-balanced multimedia applications (e.g., video telephony) that
require a similar bandwidth for both links. If the balanced services, such as voice and
video telephony, dominate the total traffic load, the cell capacity is more likely to be
determined by the reverse link.
5.2 Call Admission Strategies As described in chapter 5.1, the cell coverage and the quality of ongoing connections will
decline below the planned level, if cell interference is allowed to increase excessively.
For this reason, certain radio resource management algorithms are needed to limit the
amount of interference in the system. Call admission control (CAC or shortly AC)
regulates the establishment and modification of radio access bearers to prevent the system
from becoming overloaded. AC is used to achieve high traffic capacity and to maintain
the stability of radio access network. Here, AC is examined from the uplink point of
view. Uplink and downlink can be decoupled, since admission control decision in radio
resource management is made practically independently in uplink and downlink.
Moreover, as already pointed out, uplink and downlink are run on different basis, as the
access in the former type of link is of many-to-one instead of one-to-many in the latter
type of link.
Admission control in WCDMA is inherently different from the systems whose resources
are finite and specified. The number of channels per sector is fixed, for instance, in
frequency division and time division multiple access systems such as GSM. Thus, the
capacity limit in those systems is a hard limit, and the AC only has to take care of the
allocation of available channels, for instance, time slots for the users. CDMA has no hard
limit on the maximum capacity, which makes admission control a complex soft capacity
management problem.
The impact of admission control algorithm is significant for the performance of WCDMA
system, as the AC affects capacity, coverage and quality of service. Several admission
control strategies have been proposed in the literature[35-39]. One design choice is to
restrict the admission by fixing the amount of resources, for instance, the maximum
27
number of connections[36] or the maximum total bit rate of the cell. A SIR based policy
is introduced in [39]. There, the admission decision is made on individual basis
comparing mobile user's SIR value to the base station receiver's SIR-threshold value.
The total interference based strategy was first proposed in [35]. There, the AC blocks
calls at a base station, when the measured total power at that base station exceeds the
predetermined threshold. The total interference limiting admission controls essentially
retains the soft-capacity feature of WCDMA. In some contexts, this type of admission
control is said to convert soft capacity to semi-hard capacity[40].
It has been concluded that AC algorithms that are based on the total received power
perform best [37]. The interference-based AC supports much more users than a non-
interference AC approach because of the soft capacity utilization[36]. This is anticipated
considering the inherent interference limitation of CDMA. The advantage of the total
interference-based AC approach is intuitively the fact that all interference is treated equal
without any explicit assumptions concerning the strength of the interference source. The
total wideband interference is measured, and the admission control algorithm estimates
the load increase that the establishment of a new bearer would cause. If the new resulting
total interference would be unacceptably high, according to a predefined threshold value,
the radio access bearer request is rejected.
The approach described above directly utilizes the soft capacity feature. The less
interference that there is coming from the neighboring cells, the more capacity there is
available in the middle cell (Figure 5-1). This can be seen directly from the reuse
efficiency factor, F, in (Eq. 5-2). Some AC methods such as the throughput-based
algorithm does not implicitly take into account the interference from the adjacent cells,
but the other-cell interference is included as an estimated parameter[24]. If the
interference from other sources than the own cell is proportionally higher than assumed in
a throughput-based or a fixed-number-of-connections method, the coverage and quality
offered would be worse than estimated. In the opposite case, the system capacity becomes
under utilized. Given the complex interaction of various home-cell and other-cell noise
characteristics, the ratio of the home-cell noise to the total user noise has been argued a
very difficult parameter to estimate[41]. Interference-based admission control treats
different types of services in a uniform manner, and it is adaptive to load changes
between the cells. However, on the minus side, it may be difficult to judge precisely what
28
values should the threshold parameters, such as the maximum allowed total received
power, have. This issue will be investigated in chapters 5.4−7 using quality of service
monitoring approach.
��� �)�
Figure 5-1 (a) Soft capacity of the middle cell when cells are equally loaded (b) Soft capacity of the middle cell when there is less interference in the neighboring cells.
To allow vendor and operator specific solutions and to promote the development of
efficient algorithms, the admission control details of UMTS are not specified[26]. An
example of an interference based admission control is presented detailed in the next
chapter.
5.3 Interference based admission control strategy This chapter’s interference-based uplink admission control strategies were introduced in
[36]. The presented strategies are generic enough to illustrate the common principle of the
total interference-based methods. A method similar to the ones presented in this chapter
will be used in the simulations of chapter 6. The overall idea of the total interference-
based uplink admission control algorithm is the following: A new user will not be
admitted into the system if the estimated resulting total interference power level is higher
than the pre-specified threshold value. This is shown by (Eq. 5-3). Details, such as the
method for estimating the interference increase due to a new radio access bearer and
interference measuring methods, are different between different algorithms. The total
received power threshold, Prx_target, can be temporarily exceeded due to changes in
interference and propagation while mobile stations are moving in the network.
29
As described, a new radio access bearer is not admitted if:
ettrxrxtotalrx PPP arg__ >∆+ (Eq. 5-3)
in which Prx_total is the total uplink interference power present in the cell, ∆Prx is the
estimated increase in the interference power caused by a new user and Prx_target is the
threshold for the maximum received total interference power. Prx_total is measured from
the system, but due to short-term interference fluctuation, averaged values are actually
used in admission control.
Load factor, η, is a common measure of network congestion, and it is used in admission
control and network dimensioning. Uplink load factor is defined as follows[25]:
totalrxPnP
nPStotalrxP
S
emptySIRloadedSIR
η_
_1 ===− (Eq. 5-4)
totalrx
n
PP
_
1 −=η (Eq. 5-5)
where SIR is the signal-to-interference ratio, S is the received power at the base station of
a user and Pn denotes the system noise.
The received wideband interference, Prx_total, consists of the powers from inter-cell users,
intra-cell users and system noise:
nothrxownrxtotalrx PPPP ++= ___ (Eq. 5-6)
Using (Eq. 5-5), the above expression can be transformed into form:
η−=
1_n
totalrxPP (Eq. 5-7)
30
This expression (Eq. 5-7) is used to derive two alternative ways to calculate the total
uplink interference power increase due to a new user. First, the equations (Eq. 5-8) and
(Eq. 5-9) show a method for estimating the interference power increase using the
assumption that the power increase is the derivative of the old uplink interference power
with respect to the uplink load factor. Then, the equations (Eq. 5-10) and (Eq. 5-11) show
the integral method, in which the derivative of the total interference with respect to the
load factor is integrated from the old value.
( ) ηηηηη −=
−=
−
=111 2
_ totalnntotalrx PPPdd
ddP
(Eq. 5-8)
η
η∆
−≈∆
1_total
totalrxPP (Eq. 5-9)
η
ηηηηηηη
η
ηη
η
∆∆−−
⋅−
=−
−∆−−
=−
=∆ ∫∆+
11
111)1( 2_nnnn
totalrxPPPdPP (Eq. 5-10)
η
ηη∆
∆−−=∆
1_
_totalrx
totalrx
PP (Eq. 5-11)
In equations (Eq. 5-9) – (Eq. 5-11) ∆η is the estimated change in load factor due to a new
user. The expression for load factor of one user, Lj, has been derived in [24] and it is
obtained as:
jj
b
pj
NE
GL
υ⋅
+
=
0
1
1
(Eq. 5-12)
31
where Gp is the processing gain, υj is the channel activity factor of the user (i.e., fraction
of time during which the user's signal is present) and Eb/N0 is energy per bit to noise
power density ratio.
Lj can be estimated, since the processing gain of a user is known, channel activity factor
can be assumed and Eb/N0 is determined by the QoS requirements. Lj gives directly the
change in the total load, i.e., ∆η, which in turn gives ∆Prx_total.
5.4 Quality of Service in Interference-based Admission Control
It is already clear from chapter 5.2 that admission control is necessary to protect ongoing
calls by rejecting the access of new users, if the predicted system load would exceed the
maximum allowable value. Chapter 5.3 presented detailed example strategies to execute
an admission control algorithm in the interference-limited WCDMA. It was concluded in
chapter 5.2 that the total received interference-power based strategy is advantageous.
Nevertheless, irrespective of the admission control strategy the maximum thresholds need
to be set by some means. For instance, in the algorithm of chapter 5.3, the parameter
value Prx_target is determined by radio network planning. Selecting the best operating value
for the target is not straightforward for the following reasons: Service patterns,
quantitative and spatial user distributions may be different from cell to cell and cells
themselves exhibit a great deal of variation in the propagation due to different system
noise, shadowing and fast-fading characteristics. That is why the propagation losses
should be confirmed by field measurements. In fact, it is generally difficult to know how
real networks will respond to different thresholds at this relatively early stage of UMTS
deployment. This means that thresholds are likely to have conservative values. Therefore,
it is suggested here that the maximum allowed load of cell should not necessarily be fixed
by network planning but a dynamic method could be used instead.
The basic criterion for setting Prx_target is to define the maximum interference level that
can be tolerated by reverse link budgets to permit the network to function correctly. To
prevent the harmful effects of inappropriate thresholds, an approach to adjust the Prx_target
according to the quality of service is studied here. Quality of service based approach
considers implicitly the loading of all the cells, propagation conditions and mobile user
32
patterns, while using real-time quality monitoring as a tool to determine an effective
threshold value dynamically.
The basic idea of the proposed adaptive algorithm is to constrain the maximum total
interference at the base stations to conform to the propagation conditions and traffic of
cells. If the propagation losses and user power outage probability are smaller than
estimated, the Prx_target has been set too low. This is because mobile terminals can
compensate for the propagation loss better than anticipated under high interference. In
this case, the capacity of the system is underestimated and unnecessary blocking occurs
during heavy load situations. On the other hand, if the Prx_target has been set too high, the
mobile terminals cannot mitigate propagation channel impairments under high load.
Granting access to new connections can only make the link quality worse for the existing
calls when the system is under congestion. This increases outage probability and leads to
dropping of calls, which degrades the system performance. In this case, quality of service
should be improved and cell coverage should be increased by restricting interference
using a lower Prx_target value.
Essentially, the proposed algorithm tries to improve the system performance by
maximizing the capacity, while providing for call quality. This means that the criteria for
evaluating the system performance must be chosen. The performance factors may include
bit error rates (BER), frame error rates (FER), transmission delays, blocking probability,
dropping probability, mean bitrate, total bitrate, average queuing time etc. In this thesis,
three critical QoS metrics are considered as the main quality criteria. These are call
dropping probability, bad call probability and call blocking probability. The call dropping
probability, Pdrop, is the probability that a call that has been admitted will be terminated
prematurely before the call completion. The bad call probability, Pbad, denotes the
proportion of calls whose frame error rate exceeds the acceptable level for the service.
The probability that a new call is not admitted into the system, Pblock, is called the
blocking probability.
One approach in adjusting Prx_target is to try to maximize the capacity, while providing
acceptable QoS to the pre-specified proportion of calls. In this approach, Prx_target is
increased if the measured call dropping and bad call probability statistics are lower than
required, and it is decreased if the same statistics are greater than accepted. Clearly,
Prx_target should be raised only if good QoS has been observed under heavily loaded
33
conditions. In this thesis, the call dropping and bad call quality are taken into account
along with call blocking by defining the system performance, GoS (Grade of Service), as:
blockbaddrop PPPGoS ++= 210 (Eq. 5-13)
Call dropping has a coefficient of 10, since it is considered much more annoying than a
call blocking. The bad call probability is selected a coefficient of 2. A similar cost
function, but without the bad call term, has been used in [35], [38] and [42]. The cost
function will be minimized on cell basis in the simulations. Thus, the Prx_target of cell is
increased if:
∆−>< ettrxaverx
ettrx
PPdP
GoSdarg__
arg_
,0)( (Eq. 5-14)
where the constraint (Prx_ave > Prx_target − ∆) guarantees that the cell is heavily loaded. The
Prx_target is decreased if:
∆−>> ettrxaverx
ettrx
PPdP
GoSdarg__
arg_
,0)( (Eq. 5-15)
In the simulations, the derivative of grade of service with respect to Prx_target is
approximated by difference quotient. If the derivative cannot be calculated, as is the case
in the beginning of algorithm or when there has not been high load for some time, the
direction of Prx_target movement is defined to be determined by the dominating term of
GoS function. That is, when the observed blocking rate is larger than dropping and bad
call rates, the Prx_target is raised. On the contrary, if the dropping and bad call terms
dominate in GoS, fewer calls will be accepted by lowering Prx_target.
The motivation for the selected optimization method and the expected behaviors of call
dropping, bad call and call blocking probabilities as a function of interference are
illustrated in Figure 5-2. It is assumed in the figure that the offered load is almost
constant and great enough to cause so much interference that it is bounded by Prx_target. When the interference is great, bad call and call dropping probabilities will increase
significantly, and if the interference is forced to be low by small Prx_target, the number of
blocked calls will be excessively high. The trade-off between blocking and dropping has
34
been reported in [40] and [43]. Since the GoS function is assumed convex, the Prx_target
autotuning algorithm should ensure the global minimization of GoS function. In addition,
the algorithm is likely to drive the cell better balanced between blocking and call quality.
The system performance gains with Prx_target adaptation feature are evaluated by radio
network simulations in chapter 6.
������������
��� ����������������
����
����
�����
Figure 5-2 GoS, Pdrop,, Pbad and Pblock as a function of interference.
It is relevant to note that the Prx_target algorithm that is investigated more closely in chapter
6 is performed on cell-basis. This means one potential drawback, since interference
changes of one cell affect also the amount of interference experienced in the neighboring
cells. On the other hand, the bad effects on the other cells should remain restricted
because each cell is optimized independently. Moreover, for additional safety, the
margins within which Prx_target is allowed to move can be defined. A restricted interval
guarantees both minimum capacity and coverage. Nonetheless, cell breathing due to
other-cell interference presents a similar problem also in the fixed-interference-threshold
based strategy. The capacity and coverage of cell is always affected by neighboring cells.
A centralized scenario that takes into account other-to-own cell interference effect has
been proposed in the literature[44]. There, a fixed interference-threshold based strategy is
employed, and a user is not admitted in the cell, if it is predicted that acceptance will
increase the interference of adjacent cells above their defined thresholds. This condition is
35
undoubtedly too strict, as it blocks all the calls in the middle cell, if the interference in
any of the neighbors of the middle cell is over the threshold.
Another remark concerns wideband interference power measurements that are used as
input by admission control and Prx_target autotuning algorithm. Great care needs to be
exercised, when using observed interference values, since interference exhibits large
random short term variation caused by changing radio propagation conditions, mobile
distribution variation and system implementation details such as power control etc.[45],
[46]. The interference measurement itself is not ideal either. Thus, an appropriate filtering
method and period need to be selected for the measurements to average out the random
effects. For instance, exponential averaging can be used:
10 )1(~)1()()(~ ≤≤−⋅−+⋅= ααα iPiPiP rxrxrx (Eq. 5-16)
where P~ rx is the smoothed interference value, Prx is the latest measurement and α is the
forgetting factor.
36
6 Simulations
6.1 Simulation Setup The goal of the simulations is to study the impact of the suggested Prx_target autotuning
algorithm on the system performance and quality of service. The simulations are
conducted by a detailed dynamic system simulator. It includes traffic, mobility and
propagation models that are adopted from [47], and it implements radio resource
management functionality and algorithms described in chapter 4.
Two different scenarios are examined. In the first scenario, pure circuit-switched voice
service is simulated. The purpose of this scenario is to verify the applicability of the
algorithmic procedure. The second scenario considers mixed traffic consisting of high
priority real-time circuit-switched voice traffic and best-effort interactive packet traffic.
Here, the scalability of the autotuning feature for a more complex scheme is investigated.
The proportion of packet users of all the users is 80% in the second set of simulations.
The used traffic pattern of a packet user is typical, for instance, for www-browsing. This
will be described below in detail. Speech bit rate is 8 kbps and packet bit rates are 8, 12,
64, 144 and 512 kpbs.
Real time voice user arrivals are generated according to a Poisson random process with
independent mean call lengths of 120 seconds and with mean activity period of 3
seconds. For packet users, the session arrival is also modeled as a Poisson process. A
packet call consists of a burst of packets with each having short service duration. The
parameters that characterize packet service are: the number of packet calls in a session,
document reading time, the number of packets in a packet burst, interarrival time between
packets within a packet burst and packet size. The packet calls are also referred to as
documents. All of these parameters except packet size are modeled as geometrically
distributed random variables. The model for packet data session has been described in
[17] and [47], and is illustrated graphically in Figure 6-1.
37
-2��(�)��� ����0-�)(��-�����������
-2���-��������-���)-/����0-��/�-2��������0-�)(��-
-2��(�)��� ����0-���������0-�)(��-
-2���-��������-���)-/����0-�)(��-�
-2���3�� ������0-
Figure 6-1 Packet service model.
The packet size is modeled after a modified Pareto probability distribution function:
=
<≤⋅= +
mxβ
mxkx
kxfn
,
,)( 1
α
αα
(Eq. 6-1)
where m is the maximum allowed packet size, and parameters α and k are set to
appropriate values depending on the type of packet traffic. The β is the probability that x
≥ m, and it can be calculated straightforward from normal Pareto distribution function
without cutoff, fx(x), as follows:
1,)( >
== ∫
∞
αβα
mx m
kdxxf (Eq. 6-2)
The average, that is, expected packet size is then calculated as:
α
α
αµ ∫
∞
∞− −
−
=⋅=1
)( mkmk
dxxfx x (Eq. 6-3)
The values of the used packet parameters are given in Table 6-1.
38
Table 6-1 Packet traffic parameter values.
Mean number of packet calls per session 5
Mean reading time between packet calls in seconds 5
Mean number of datagrams within a packet call 75
Mean interarrival time between datagrams in seconds
0.0100
k of Pareto distribution 81.5
α of Pareto distribution 1.1
Maximum allowed packet size in bytes 66666
Mean packet size in bytes 480
The used propagation model is a subset of a Helsinki scenario with imported propagation
data used for a planning tool. The plan consists of 7 sites and total of 17 cells. The user
arrivals are distributed uniformly over the simulation area and the users move along the
streets.
The simulations are run in a heavy load condition in order to study the quality of service
sensitivity of cells to different Prx_target levels. The generated load needs to be high enough
to keep the interference at maximum level, that is, near or above Prx_target. This is because
the system performance is sensitive for the admission control thresholds only when
interference is great. Total of 2800 mobile stations are generated for the first scenario and
3000 users for the second scenario, which means that at least some cells should be
congested. The scenario is planned so that the load will not be distributed equally
between the cells.
There are various alternatives for the admission control to operate in the mixed service
case. One way to exploit the difference between the real-time conversational service and
interactive packet service is to prioritize the real-time traffic using resource reservation
policy. In the resource reservation policy, part of the system resources is shared, meaning
that either of the two types of services may use them if they are free. Nonetheless, the
39
conversational service has priority over the interactive service, so that in the case of
contention, resources are assigned to real-time radio access bearers up to a specified
threshold. However, part of the capacity is strictly reserved to the interactive service only
to always provide some quality also for non-real time packet traffic. Resource reservation
policy is described in [48].
Another common scheduling strategy is pre-emption scheme, which is also the admission
control policy selected for the simulations. In the pre-emption scheme conversational
sessions are admitted unless all resources are already used by other conversational
bearers. Interactive sessions get resources only if there is some capacity left over from the
conversational or other circuit-switched sessions. This type of scheduling has been
described in [24] and [48]. The pre-emption policy is depicted in Figure 6-2.
������������������������������
��� �)�
�����(���
���0-�"*!�
#��"*!�
Figure 6-2 (a) Pre-emption scheme with low load. Resources are allocated to CS and packet traffic. (b) Pre-emption scheme with high load. CS traffic has priority over packet traffic. Note that interference may temporarily exceed the Prx_target.
The core of the autotuning algorithm was described in chapter 5.4. In the simulations,
load limits are adjusted according to the measured quality of service after each simulation
round. The Prx_target is initially set 3dB above noise level. It is a conservative value that
40
can been used in a macro environment At each iteration, the number of initiated calls, as
well as the number of dropped, bad and blocked calls are collected on cell basis. The
value of Prx_target in a cell is gradually reduced if the load is high and the cost caused by
bad quality and dropping can be decreased more than the cost caused by blocking is
increased. On the other hand, if the load is high and blocking rate cost change dominates
the weighted bad quality and dropping rate cost change, the Prx_target will be raised. The
step size for movements of Prx_targt is 0.5dB during the first iterations and 0.25dB in the
later phase if the grade of service begins to stabilize.
In the simulations, a connection is considered dropped if consecutive frame errors will
last more than 5 seconds. Moreover, a bad speech call is defined to have mean frame
error rate of more than 2%. Interactive packet calls are not very sensitive to frame errors
and bad packet calls are ignored in the results. Here, for simplicity, a dropped connection
is considered as belonging to all the base stations with which it has soft handover at the
end of call. This is not necessarily a proper assumption in real network, where only the
prevailing cell, that is, the cell with the strongest link should be considered. Of course,
this would require a more complex and heavier implementation of radio network statistics
collection. Moreover, to avoid bias in bad call measurements caused by soft handover, the
statistics should be collected periodically.
The most important simulation parameters can be found in table format in Appendix B.
Many of those parameters are not separately mentioned here but they will all have effect
on the collected quality of service values. Twelve simulations will be conducted for both
scenarios. Each simulation run lasts for 15 minutes simulated time.
6.2 Results
6.2.1 Scenario 1: Speech
Here, the simulation results are given for the first scenario. In Figure 6-3 and Figure 6-4,
the system performance in terms of grade of service, proportion of blocked calls and
weighted bad quality are depicted versus simulation round. Figure 6-3 shows the results
for the overall system and Figure 6-4 for the individual cells.
41
The first observation is that the cells are capable of serving more calls with satisfactorily
quality of service when running the Prx_target autotuning algorithm. The defined grade of
service improved significantly and the proportion of blocked calls almost halved after 11
rounds of simulations. The second observation is that the overall system performance is
improved only moderately during the last iterations, and that there remains some quality
and capacity problems at the end of simulations. The main reason for this is the fact that
two cells, 8 and 13, are very heavily loaded. This means that these cells have necessarily
a large number of bad and blocked calls when the load is that high. There does not exist
any single value for Prx_target that will perfectly solve quality and capacity problems in
these cells. The considerable quality problems of cells 8 and 13 have much influence on
the overall system performance. However, other cells perform well at the end of
simulations and even the performance of cell 13 is constantly improving. Thus, the
algorithm has not converged after 11 simulations.
One reason that will probably make the final fine tuning difficult is due to the
simplification made when counting bad and dropped calls as explained in chapter 6.1.
That is, the link strength is not properly accounted for when associating bad and dropped
calls with the cells. In any case, it can be seen that the system and the individual cells
behave in a more fair and efficient manner when it comes to quality of service. The
blocking rate has decreased extensively in many of the cells and bad quality has not
increased drastically in any of the cells.
42
0 1 2 3 4 5 6 7 8 9 10 110
5
10
15
20
25
30
35
simulation no
[%]
GoS blocked 10*Pdrop+2*Pbad
Figure 6-3 Grade of Service, proportion of blocked calls and weighted proportion of bad quality and dropped calls versus simulation round for the overall system in scenario 1.
0 5 100
10
20
0 5 100
2
4
0 5 100
2
4
0 5 100
10
20
0 5 100
2
4
0 5 100
2
4
0 5 100
10
20
0 5 100
20
40
60
80
0 5 100
10
20
0 5 100
2
4
0 5 100
2
4
0 5 100
10
20
0 5 100
20
40
60
80
0 5 100
2
4
0 5 100
10
20
0 5 100
10
20
simulation no
[%]
GoSblocked10*Pdrop+2*Pbad
cells 1−16
Figure 6-4 Grade of Service, proportion of blocked calls and weighted proportion of bad quality and dropped calls versus simulation round for the individual cells 1-16 in scenario 1.
43
The comparison of Prx_target values between the first iteration round and after the last
iteration round is shown in Figure 6-5. The cell loading factor, η, which a convenient way
to refer to the utilized capacity, is given in Figure 6-6. The results show that the utilized
capacity has increased significantly in most of the cells and has not diminished in any of
the cells. The maximum interference target has increased in all of the cells.
0 2 4 6 8 10 12 14 160
1
2
3
4
5
6
7
cell no
Prx
targ
et [d
B]
in first simulationafter last simulation
Figure 6-5 Prx_target movements during the iterations in simulation scenario 1.
44
0 2 4 6 8 10 12 14 16
0.2
0.3
0.4
0.5
0.6
0.7
0.8
cell no
load
fact
or
iteration 11iteration 5iteration 0
Figure 6-6 Cell loading factor iteration0, iteration6 and iteration11 for simulation scenario 1.
The mobile transmit power distributions are shown in Figure 6-7. It can be concluded that
the power distribution curve has moved to the right, but that there is no drastic increase in
average transmit powers. Finally, it is examined, with the help of Figure 6-8, where the
quality failures have occurred in the first simulation (picture above) and in the last
simulation (picture below). It can be seen that blocked calls have almost totally vanished
from large areas. The locations where bad and dropped calls are concentrated remain
roughly the same after adjusting Prx_target.
45
−40 −30 −20 −10 0 10 200
0.005
0.01
0.015
0.02
0.025
0.03
0.035
0.04
MS uplink transmission power [dBm]
freq
uenc
y
iteration 11iteration 5iteration0
Figure 6-7 Mobile station power distribution for iteration0, iteration6 and iteration11 in scenario1.
−160
−140
−120
−100
−80
1000 1500 2000 2500 3000 35000
500
1000
1500
2000
x−coordinate [m]
y−
co
ord
ina
te [m
]
0
12
3
45
67
8910
11
12
1314
1516
blocked callbad or dropped callbase station sector
−160
−140
−120
−100
−80
1000 1500 2000 2500 3000 35000
500
1000
1500
2000
x−coordinate [m]
y−
co
ord
ina
te [
m]
0
12
3
45
67
8910
11
12
1314
1516
blocked callbad or dropped callbase station sector
path loss [dB]
path loss [dB]
Figure 6-8 Propagation conditions, base station sectors, bad, dropped and blocked calls for simulation number 0 (picture above) and simulation number 11 (picture below) in scenario 1.
46
Generally, the results of the first simulation scenario indicate that the system performance
can be optimized and managed by the dynamic adjustment of Prx_target. Moreover, it can
be seen that a better behavior in one cell does not occur at the expense of the adjacent
cells' performance.
6.2.2 Scenario 2: Mixed Case
In the second scenario, a mix of circuit-switched speech and interactive packet traffic was
simulated. Figure 6-9 shows the overall system performance as a function of simulation
round. The performance of the individual cells is illustrated by Figure 6-10. Figure 6-11
shows Prx_target changes and Figure 6-12 cell loading factor movements. It can be seen that
the results are similar to the first simulation scenario. The autotuning has improved the
system and cell performance to some degree. The blocking has decreased greatly and the
weighted bad quality (10Pdrop+2Pbad) has increased only slightly. Consequently, the
defined grade of service is also better after running the autotuning algorithm. The
simulations of scenario 2 support the conclusion that the Prx_target autotuning method is
general enough to be applicable and beneficial in various scenarios.
0 1 2 3 4 5 6 7 8 9 10 110
5
10
15
20
25
30
35
simulation no
[%]
GoSblocked10*Pdrop+2*Pbad
Figure 6-9 Grade of Service, proportion of blocked calls and weighted proportion of bad quality and dropped circuit-switched calls versus simulation round for the overall system in scenario 2.
47
0 5 100
10
20
30
0 5 100
2
4
0 5 100
2
4
0 5 100
10
20
30
0 5 100
2
4
0 5 100
2
4
0 5 100
10
20
30
0 5 100
50
100
0 5 100
10
20
30
0 5 100
2
4
0 5 100
2
4
0 5 100
10
20
30
0 5 100
50
100
0 5 100
2
4
0 5 100
10
20
30
0 5 100
10
20
30
simulation no
[%]
GoSblocked10*Pdrop+2*Pbad
cells 1−16
Figure 6-10 Grade of Service, proportion of blocked calls and weighted proportion of bad quality and dropped circuit-switched calls versus simulation round for the individual cells 1-16 for scenario 2.
0 2 4 6 8 10 12 14 160
1
2
3
4
5
6
7
cell no
Prx
targ
et [d
B]
in first simulationafter last simulation
Figure 6-11 Prx_target movements during the iterations in simulation scenario 2.
48
0 2 4 6 8 10 12 14 16
0.2
0.3
0.4
0.5
0.6
0.7
0.8
cell no
load
fact
or
iteration 11iteration 5iteration 0
Figure 6-12 Cell loading factor iteration0, iteration6 and iteration11 for simulation scenario 2.
49
7 Conclusions It was shown in this thesis that by autotuning the maximum received uplink power
threshold the system performance can be improved and managed by network monitoring
and appropriate quality of service statistics. Thus, the autotuning can be useful for the
operators that want to make the optimum use of the scarce resource of spectrum.
Nevertheless, it is difficult to draw a firm conclusion, based on the simulation trials
conducted here, how well the algorithm would behave in real network. In real network,
there exists a greater variety in traffic load, mobile speeds and traffic classes and more
measurement error than in the conducted simulations. Probably, a more advanced
algorithm is needed to account for load variations, soft handover, fast-moving mobiles,
various traffic types and different QoS requirements. However, to be practical the
algorithm should have low complexity of implementation and low volume of control
signaling. If the autotuning is to be employed, great care needs to be exercised to avoid
opening up coverage holes between cells that may arise when the thresholds are moved.
It is also difficult to make a general estimation of how much can be obtained with the
quality of service based threshold autotuning, as the gain depends entirely on the network
characteristics. If network planning and dimensioning can be made accurately, the
maximum interference threshold can be set with confidence. Consequently, in that case,
there is no demand for autotuning. However, the traffic characteristics and radio
environment of real network can be different from those expected. Moreover, in the
beginning phase of the third generation WCDMA networks, the threshold values are
based on small scale simulations and engineering judgment. This could mean that the
thresholds do not have optimal values initially, which gives needs for autotuning. It
should also be remembered that the uplink performance optimization is critical only when
uplink is the limiting link of the network.
Applications emerging from Internet are increasingly capable of defining the required
QoS level. The current trend in UMTS development is toward an all-IP UMTS, which
means that all the circuit-switched transport technologies will eventually be replaced by
packet-switched transport technologies [49]. This development together with the demand
50
for good capacity utilization set a requirement to implement means to monitor and control
the quality of air interface traffic.
Mobile Internet and wide variety of services in the third generation WCDMA mobile
systems make the network resource management very challenging. Because a specific
maximum interference autotuning algorithm depends on the exact details and the desired
behavior of the system, only the core of the algorithm is stated in this thesis. However,
the general concept of the autotuning algorithm is supposed to remain and apply in
different scenarios: The maximum interference threshold can be raised to increase
capacity if the required QoS can be guaranteed, and the maximum interference threshold
can be decreased if QoS and coverage need to be improved at the expense of some
capacity reduction. Further research is obviously required to develop an optimal
algorithm for a specific network.
51
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56
Appendices:
A. Abbreviations
3G Third generation
3GPP 3rd generation partnership project
AC Admission control
BPSK Binary phase shift keying
BS Base station
BTS Base transceiver station
CAC Call admission control
CDMA Code division multiple access
CN Core network
CS Circuit switched
DL Downlink
DS-CDMA Direct sequence CDMA
DS-SS Direct sequence SS
DTX Discontinuous transmission
ETSI European telecommunications standards institute
FDD Frequency division duplex
FDMA Frequency division multiple access
FH-SS Frequency hopping spread spectrum
GGSN Gateway GPRS support node
GMSC Gateway MSC
GPRS General packet radio system
GSM Global system for mobile communications
HC Handover control
HCS Hierarchical cell structure
57
HLR Home location register
HO Handover
IEEE Institute of electrical and electronic engineers
IMT-2000 International mobile telephony 2000
IT Information technology
ITU International telecommunications union
IP Internet protocol
LAN Local area network
LC Load control
ME Mobile equipment
MS Mobile station
MSC Mobile services switching center
MSK Minimum phase shift keying
MUD Multiuser detection
Node B UMTS Base station
PC Power control
PDF Probability distribution function
PLMN Public land mobile network
PN Pseudo noise
PS Packet schduler, Packet switched
PSK Phase shift keying
QoS Quality of service
QPSK Quadrature phase shift keying
RAN Radio access network
RAB Radio access bearer
RNC Radio network controller
RNS Radio network sub system
RRM Radio resource management
RTT Radio transmission technology
58
SDU Service data unit
SIM Subscriber identity module
SIR Signal to interference ratio
SGSN Serving GPRS support node
SHO Soft handover
SMS Short message service
SS Spread spectrum
TDD Time division duplex
TDMA Time division multiple access
TPC Transmitter power command
TS Technical specification
UE User equipment
UL Uplink
UMTS Universal mobile telecommunication system
USIM UMTS Subscriber identity module
UTRAN UMTS Terrestrial radio access network
VcoIP Video conferencing over IP
VLR Visitor location register
VoIP Voice over IP
WCDMA Wideband code division multiple access
WWW World wide web
59
B. Simulation Parameters
Parameter Name Value
Carrier frequency [GHz] 2.0
Bandwidth [MHz] 5.0
Chip rate [kbps] 3840
Propagation Model Subset of a Helsinki Scenario, imported
propagation data
Number of cells 17
Number of operators 1
Number of radio network controllers 1
Terminal speed [km/h] 3
Uplink system noise [dBm] -102.9 (constant)
Maximal MS output power [mW] 125
MS dynamic range [dB] 65
Speech user bit rate [kbps] 8
Packet user bit rates [kbps] 8, 12, 64, 144, 512
Maximum number of terminals in the area (scenario 1: 2800, scenario 2: 3000)
User proportions (scenario 1: 1.0, scenario 2: 0.8 / 0.2)
Call arrival rate [calls/user/hour] 0.004167
Averaging window for Prx [slots] 32 (memoryless filter with forget factor 0.1)
Average speech call length [s] 120
Minimum speech call length [s] 7
Average DTX speech burst period [s] 3
Average packet call length [s] 40
Mean number of packet calls in session 5
Mean thinking time in call [s] 5
60
Mean number of packets in call 75
Average packet interarrival time in call [s] 0.0100
Maximum packet size [bytes] 66666
Average packet size [bytes] 480
Maximum active set size in SHO 3
Addition window in SHO [dB] 1
Drop window in SHO [dB] 3
Outer loop power control step size [dB] 0.3
Dropped call criteria Consecutive erroneous frames over 5 sec
Bad call criteria FER-rate over 2 % over the whole call
Outerloop PC FER threshold for speech [%] 1
Initial SIR threshold at base station [dB] 6.5
Mobile station power control step [dB] 1