Smart Antenna in 3G Networks

Syed Abdul Basit Advisor: Engr. Tabeer H. Ikram

College of Engineering

Pakistan Air Force - Karachi Institute of Economics & Technology, Korangi Creek

Karachi – 74190 (Pakistan)

sabasit2006@gmail.com

Abstract The technology of smart antenna for mobile

communications has received enormous interest

worldwide in recent decade, especially in WiMax.

A smart antenna forms a pattern that adapts to the

current radio conditions improving the

communication link. The main reason for applying

smart antennas is the possibility for a large

increase in capacity and to introduce new services.

The purpose of this paper is to give an introduction

of smart antennas in 3G networks, its algorithms

used in creating beamforming patterns, how the

cell capacity and coverage improves, and what

benefits will get from it.

Keywords: Smart Antennas (SA), Adaptive

Antennas (AA), Switched Beam Antennas.

1. Introduction

With the development of mobile

communication industry, frequency resources

are becoming a bottleneck for mobile service

operators, which will be more severe as

subscribers increasing at explosive rate [1].

Base station antennas have up till now been

omnidirectional or sectored. This can be

regarded as a "waste" of power as most of it

will be radiated in other directions than toward

the user. In addition, the power radiated in

other directions will be experienced as

interference by other users. The idea of smart

antennas is to use base station antenna patterns

that are not fixed, but adapt to the current

radio conditions. This can be visualized as the

antenna directing a beam toward the

communication partner only. The difference

between the fixed and the smart antenna

concept is illustrated in Figure 1.

Smart antennas will lead to a much more

efficient use of the power and spectrum,

increasing the useful received power as well as

reducing interference.

The purpose of smart antenna is to transform

its main lobe and gain into the desired

direction through automatic means.

2. Smart Antennas Basic Concepts

Antenna Elements: The functions of SA are

conducted by both antenna array as well as

base-band digital signal processor [5]. The

elements can be arranged in many structures,

such as uniform linear array (ULA), uniform

Figure 1: Range extension using an adaptive antenna [2]

circle array (UCA), etc. The distance between

two elements is half of wavelength, which

showed in Figure 2 and Figure 3.

SA utilizes 4 to 16 antennas structure and

makes element distance 1/2 wavelengths in

FDD (Frequency Division Duplexing) mode

and 5 wavelengths in TDD (Time Division

Duplexing) mode [6].

SA verdicts the direction of arrival of user

signal (i.e. DOA estimation) by means of

digital signal processing technology, as well as

forms an antenna main beam in this direction.

The elevation angle of main beam to each

antenna element is identical, and its azimuth

angle diagram is controlled by base-band

processor which produces a large number of

beams simultaneously. According to the

distribution of users, beams are formed in the

range of 360 [7].

Beamforming is the method used to create the

radiation pattern of the antenna array by

adding constructively the phases of the signals

in the direction of the targets/mobiles desired,

and nulling the pattern of the targets/mobiles

that are undesired/interfering targets. This can

be done with a simple FIR tapped delay line

filter. SA utilizes digital method to fulfill

beamforming, i.e. DBF (Digital Beam

Forming) antenna, which makes adaptive

algorithm update in software designing and

makes system more flexible on the premise

not changing system hardware configuration [5]. And then DBF summates the weighted

antenna signals to process formed antenna

beams, of which main beam aims at expected

users and zero point aims at interference

directions.

Sectorization schemes, which attempt to

reduce interference and increase capacity, are

the most commonly used spatial technique that

have been used in current mobile

communications systems for years. Cells are

broken into three or six sectors with dedicated

antennas and RF paths. Increasing the amount

of sectorization reduces the interference seen

by the desired signal. One drawback of current

sectorization techniques is that their efficiency

decreases as the number of sectors increases

due to antenna pattern overlap. Furthermore,

increasing the number of sectors increases the

handoffs the mobile experiences while moving

across the cell. Compare this technique to that

of a narrow beam being directed towards a

desired user. It is clear that some interference

that would have been seen by the existing

120° sector antenna will be outside the

beamwidth of the array. Any reduction in the

interference level translates into system

capacity improvements. Smart antennas could

be divided into two major types, fixed

multiple beams and AA systems. Both systems

attempt to increase gain in the direction of the

user. This could be achieved by directing the

main lobe, with increased gain, in the direction

of the user, and nulls in the directions of the

interference [3, 4]

.

3. Types of Smart Antennas

Smart Antennas consists of switched beam

antenna and adaptive array antenna. Switched

beam antenna can cover entire user cell by

means of several parallel beams whose

direction is fixed and beamwidth is decided by

the number of antenna elements [5]. Taking

advantage of base-band digital signal

processing technology, adaptive arrays allow

the antenna to steer the beam to any direction

of interest while simultaneously nulling

interfering signals.

Figure 2: 4-element ULA [5]

Figure 3: 8-element UCA [5]

Switched Beam Antennas: The switched beam

method is considered an extension of the

current cellular sectorization scheme. The

switched beam approach further subdivides

the macro-sectors into several micro-sectors.

Each micro-sector contains a predetermined

fixed beam pattern with the greatest gain

placed in the center of the beam. When a

mobile user is in the vicinity of a micro-sector,

the switched beam system selects the beam

containing the strongest signal. During the call,

the system monitors the signal strength and

switches to other fixed beams if required.

Adaptive Arrays: The main advantage of

adaptive antenna arrays compared with

switched beam antennas is their ability to steer

beams towards desired users and nulls toward

interfering signals as they move around a

sector. Several beamforming approaches exist

with varying degrees of complexity. A

conventional beamformer or delay-and-sum

beamformer has all the weights of equal

magnitudes. To steer the array in a particular

direction, the phases are selected appropriately.

In order to be able to null an interfering signal,

the null-steering beamformer can be used to

cancel a plane wave arriving from a known

direction producing a null in the response

pattern at this direction. See Figure 4 and 5.

4. Weight Adaptation Algorithms

In the beamforming case the major question is:

How to calculate the complex weights w the

individual antenna elements for each user?

Before answering this question one should

reflect upon the different processes in the

baseband signal processing unit, before the

antenna weights can be adapted. Basically the

signal processing unit is responsible for the

user identification, user separation and beam

forming. First, the base station has to estimate

the directions of arrival of all multipath

components. Next, it has to determine whether

the echo from a certain direction comes from a

desired user or from an interferer. Finally, it

can compute the antenna weights in order to

increase the SNIR as much as possible [11]

.

Adaptation algorithms are designed to process

the above mentioned demands. They can

basically be classified as temporal reference

(TR), spatial reference (SR) and blind (BA)

algorithms.

4.1 Temporal Reference Algorithms

TR algorithms are based on the prior

knowledge of the time structure of parts of the

received signals. The training sequences of

both 2G and 3G systems fulfill this

requirement. The receiver adjusts the complex

weights in such a way that the difference

between the combined signal at the output and

the known training sequence is minimized.

Those weights are then used for the reception

of the actual data [11]

.

Figure 4: Switched multibeam antennas

has fixed beam pattern [10].

Figure 5: Adaptive antenna array has variable beam

pattern depend upon the location of the user [10].

4.2 Spatial Reference Algorithms

SR algorithms estimate the direction of arrival

(DOA) of both the desired and interfering

signals. They are based on the prior

knowledge of the physical antenna geometry.

In most mobile communication systems, the

time a wavefront takes to pass through the

antenna array is much smaller than the bit (or

chip) interval Tb [11]

.

4.3 Blind Algorithms

Instead of using a training sequence or the

properties of the receiver array, “blind”

algorithms can be applied for weight

adaptation as well. Blind Algorithms basically

try to extract the unknown channel impulse

response and the unknown transmitted data

from the received signal at the antenna

elements. Even though they do not know the

actual bits, Blind Algorithms use additional

knowledge about the structure of the

transmitted signal, e.g. finite alphabet [11]

. If

training sequences are used in combination

with blind algorithms, they are called semi-

blind algorithms which show better

performance than temporal reference

algorithms or blind algorithms alone [9].

5. Strategies For Coverage &

Capacity Improvement

Smart antennas can increase the coverage area

and/or the capacity of a wireless

communication system. The coverage, or

coverage area, is simply the area in which

communication between a mobile and the base

station is possible. The capacity is a measure

of the number of users a system can support in

a given area. Three strategies that employ

smart antennas, which are range extension:

increase coverage, while the interference

reduction/rejection and spatial division

multiple access (SDMA) approaches seek to

increase the capacity of a system.

5.1 Range Extension

In sparsely populated areas, extending

coverage is often more important than

increasing capacity. In such areas, the gain

provided by adaptive antennas can extend the

range of a cell to cover a larger area and more

users than would be possible with

omnidirectional or sector antennas. This

approach is shown in Figure 1.

5.2 Interference Reduction & Rejection

In populated areas, increasing capacity is of

prime importance. Two related strategies for

increasing capacity are interference reduction

on the downlink and interference rejection on

the uplink [2]. To reduce interference,

directional beams are steered toward the

mobiles. Interference to co-channel mobiles

occurs only if they are within the narrow

beamwidth of the directional beam. This

reduces the probability of co-channel

interference compared with a system using

omnidirectional base station antennas.

Interference can be rejected using directional

beams and/or by forming nulls in the base

station receive antenna pattern in the direction

of interfering co-channel users. Interference

reduction and rejection can allow Nc (which is

dictated by co-channel interference) to be

reduced, increasing the capacity of the system [2].

Interference reduction can be implemented

using an array with steered or switched beams.

By using directional beams to communicate

with mobiles on the downlink, a base station is

less likely to interfere with nearby co-channel

base stations than if it used an omnidirectional

antenna. This is depicted in Figure 7.

5.3 Spatial Division Multiple Access

Smart antennas also allow a base station to

communicate with two or more mobiles on the

same frequency using space division multiple

access (SDMA). In SDMA, multiple mobiles

can communicate with a single base station on

the same frequency. By using highly

directional beams and/or forming nulls in the

directions of all but one of the mobiles on a

frequency, the base station creates multiple

channels using the same frequency, but

separated in space [2]. This approach is shown

in Figure 8.

6. Benefits Smart Antennas can be used to achieve

different benefits. The most important is

higher network capacity, i.e. the ability to

serve more users per base station, thus

increasing revenues of network operators, and

giving customers less probability of blocked

or dropped calls [11]

. Also, the transmission

quality can be improved by increasing desired

signal power and reducing interference. A

schematic model of how Smart Antennas work

is shown in Figure 9.

7. Application Of SA in 3G Base

Stations As an important measurement of enhancing

communications system capacity, SA is

mainly used in base stations. Future operation

frequency in mobile communications system

will be higher and the size of antenna will be

smaller provided half wavelength antenna

element gap. Now I introduce what SA brings

for 3G base station as follows [8]:

7.1 Forming many beams It takes SA in base station forming many

beams to cover entire cell as an example. A

cell can be covered by 3 beams with 120 ° or 6

beams with 60 ° width. Each beam can be

treated as an independent cell. When a MS

(Mobile Station) leaves a beam covering area

for another, the beam will conduct a

handoff [5].

7.2 Forming adaptive beams SA can locate each MS and form the beams

covering a MS or MS groups. Thus, each

beam may be taken as an intra-frequency cell

in order that variable traffic can be covered by

changing the shape of beams dynamically.

When a MS is moving, it is very favorable to

Figure 7: Interference reduction using adaptive

antennas (directional beams interfere

with fewer cells) [2]

Figure 8: Spatial division multiple access

(SDMA) using adaptive antennas [2]

Figure 9: Smart antenna patterns in a multi-service

UMTS system with high data rate interferers and

desired low data rate users [11].

control BS transmit power if we select

different beams to cover every MS groups,

which is available when MS’s are moving in

groups or restricted routines [5].

7.3 Forming beam null By virtue of the difference in incident angels

between desired signals and jamming signals,

SA may choose proper merging weights to

form correct antenna receiving mode (i.e.

main lobe focus on desired signals and side

lobe focus on main jamming signals) for the

purpose of reducing interference more

effectively and reducing frequency reuse

efficiency in higher proportion. In some sense,

SA is a more flexible fan antenna with a

narrower main lobe [5].

7.4 Forming dynamic cell The concept of adaptive beamforming can be

generalized to dynamic variation of cell shape,

which demands for SA having the capabilities

of positioning and tracing MS to adjust system

parameters adaptively to meet business

requirements. It shows that SA can change cell

border and assign some channels for each cell

dynamically thereby [5].

8. Conclusion From a technology point of view, smart

antennas can be seen as an extension of the

"conventional" resource allocation schemes

used in radio communications. In addition to

dividing the space into cells, it will now also

be possible to employ space division inside

each cell. Different degrees of utilization of

the spatial dimension are possible, and

different steps have been described here.

Smart antenna technology is a broad concept

and implementations range from simple

techniques that involve switching between

lobes to advanced algorithms maximizing the

received signal-to-interference ratio.

Implementation of smart antennas is done

using array antennas. The techniques for

beamforming with array antennas are well

known, and must be employed in both duplex

directions for the improvements to be

substantial. However, with rapid channel

variations it is not a trivial task to provide

optimum beamforming, especially for the

downlink direction.

The use of smart antennas is not purely a radio

transmission issue. It also influences network

services such as handover and connection

setup. Introducing the spatial domain in the

resource management system makes this more

complex.

Several smart antenna testbeds and field trials

have been set up and run by manufacturers

and research institutions. The first tests

allowing commercial traffic over a base

station employing smart antennas were

performed by Ericsson and Mannesmann

Mobilfunk in Germany in the autumn of

1998 [2].

Smart antennae are used for many applications,

especially now a days in Wi-Max. They are

used notably in acoustic signal processing,

track and scan RADAR, radio astronomy and

radio telescopes, and mostly in cellular

systems like W-CDMA and UMTS

References

[1] Lal C.Godora. Application of antenna

arrays to mobile communications, Part

I: Performance improvement,

feasibility, and system consideration.

Proceedings of the IEEE, July 1997,

85(7): 1031-1060.

[2] W. L. Stutzman and G. A. Thiele,

Application of Smart Antennas to

Mobile Communications Systems

[3] Rappaport, T. S., (ed.), Smart

Antennas: Adaptive Arrays,

Algorithms and Wireless Position

Location, New York: IEEE Press,

1998.

[4] Tsoulos, G.V., (ed.), “Adaptive

Antennas for Wireless

Communications,” IEEE Press, 2001.

[5] XIAO Jian, YU Lei, Smart Antenna

technology in 3G system, Journal of

Communication and Computer,

ISSN1548-7709, Volume 4, No.7

(Serial No.32), USA, Jul. 2007.

[6] Bellofiore, S., Foutz, J., Balanis, C.A.,

Spanias, A.S. Smart-antenna systems

for mobile communication networks,

Part 2: Beamforming and network

throughput. Antennas and Propagation

Magazine, IEEE, Aug 2002, 44(4):

106-114.

[7] LI Shi-he. The principles and

realization of smart antennas.

Telecommunication Construction,

2001, (4): 22-26.

[8] WANG Ji-feng. Smart antenna

technology based on software radios.

Journal of Nanjing University of Posts

and Telecommunications: Natural

Science, 2001: 45-47.

[9] J. Laurila, Semi-Blind Detection of

Co-Channel Signals in Mobile

Communications , PhD thesis,

Technische Universität Wien, March

2000, www.nt.tuwien.ac.at/mobile/

[10] Jack H. Winters, SMART Antennas

For Third Generation TDMA, AT&T

Labs - Research, Middletown, NJ

07748, November 27, 2000

[11] Symena Software & Consulting,

Smart Antennas – A Technical

Introduction