measurement reports based cell planning

7/28/2019 Measurement Reports Based Cell Planning

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Scope of the Document

In a GSM network same frequencies need to be used

in several BSs. This implies that in practice, every cell

has other cells nearby whose radio transmission will

interfere with the desired signal.

Careful selection of used frequencies in each cell is

needed to achieve sufficient quality in the network.

This is called frequency planning.

The quality of the frequency plan will affect the

capacity of the network.

In the network setup phase, the frequency plan has to

be made based on radio wave propagation

predictions and small scale ad-hoc measurements.

In this work, a method to optimize an existing

frequency plan in an operational GSM network isstudied. The method is based on standardized

functionality in GSM called mobile measurement

reporting.

MMRs can be stored and post-processed to obtained

information about potential interference between any

pair of cells in the network. In this work, the

measurement based data is shown to be more

accurate than what is obtained through current radio

wave propagation models.

There are several ways to post-process the raw data

available from MMRs. The result of this processing is

called an Interference Matrix.

Different post-processing techniques lead to different

meanings of IM elements.

It is concluded in this work that frame erasure rate

(FER) should be the quantity used in IM. FER is a

measure that correlates strongly with subjective

voice quality.

The raw data from MMRs is subject to limitations

mainly due to limited number of bits available for theair interface signaling. Only top six measurement

values are reported.

Furthermore, these values are truncated. These

limitations lead to inaccuracies in the data available

for frequency planning. In this thesis, the inaccuracies

are found to be smaller than those in the prediction

based data.

GSM Channel Structure

A term channel is used very loosely in GSM. It can be

physical or logical.

Frequency Band used by GSM

The original band reserved for GSM900 is from 890

MHz to 915 MHz to UL (from MS to BTS) and from

935 MHz to 960 MHz for DL. Later, to increase the

capacity, GSM 1800 and EGSM900 (Extended) bands

were allocated.

Physical Channels

The GSM uses Frequency (FDMA) and Time division

(TDMA) as a multiple access technique.

Spacing between GSM frequencies is 200 kHz. The

time domain is split into 8 sequential slots, called

Timeslots (TS).

Therefore, each frequency can support up to 8 users

simultaneously.

Time Division also means that during a call, mobile

has to transmit only 1/8th of the time. Receiving isscheduled to always happen 3 TS before

transmission.

Frame Structure

Each burst period is roughly 577 s. 8 bursts

(corresponding each to different physical channel)

make up 1 TDMA frame.

TDMA frames have running index (common in cell

area) for each logical connection, which is used for

example in encryption.

26 TDMA frames form one 26 multi-frame and 51

TDMA frames corresponding form 51 multi-frame.

26 51-multiframes constitute a super-frame, lasting

about 6.2 seconds. 2048 super-frames form a hyper-

frame, which is the longest cycle in the GSM frame

hierarchy.

Normal Burst structure (there are 3 more burst types

not discussed here) shown in figure 5 consists of 26

bit training sequence, which is essential for the

demodulation.


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Surrounding training sequence are the two individual

bits called stealing flags. These indicate if either 57 bit

information blocks is actually stolen to signaling

purposes requiring quick attention, like HO

commands.

Both 3 bit blocks called tail bits, surrounding

information bits, are always set to 0. Finally in the endof the burst, there is 8.25 bit guard period.

Logical Channel

Logical channels are defined functions supported by

Physical channels. Each physical channel can carry

many logical channels. These can be divided to

dedicated and common channels.

Further division can be made between traffic and

control channels.

Traffic Channels (TCH)There are 2 traffic channels, TCH/F (Traffic Channel/

Full Rate) and TCH/H (Half rate). TCH/F can support


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speech at net rate of 13 kbit/s or data with rates of

2.4 kbit/s (TCH/F2.4), 4.8 kbit/s (TCH/F4.8) or 9.6

kbit/s (TCH/F9.6) and requires one physical channel.

TCH/H carries speech with second generation voice

coder at a net rate of 6.5 kbit/s or data with rates 2.4

kbit/s or 4.8 kbit/s.

2 TCH/Hs can occupy one physical channel. Control

channels can be divided to broadcast channels (BCH),

common control channel (CCCH) and dedicated

control channels (DCCH).

Broadcast Channels (BCH)BCCH (Broadcast Control Channel) is responsible for

general broadcast functions. MS requires information

from network to be able to function efficiently.

MS might be able to receive many cells from differentGSM networks. For example, network identification is

regularly sent on the BCCH channel. BCCH channel

uses always time slot 0 and DL direction only.

FCCH (Frequency Correction Channel) sends pre-

determined bursts to DL direction only which mobile

knows to look for. In fact, it is because of FCCH that

mobile can synchronize its internal timeslot

boundaries with those of the BTS.

Mobile can also correct the frequency of its internal

time base to help in demodulation of other channel

bursts.

After finding the FCCH, mobile also knows the

location of the synchronization channel (SCH) since

relative position of these two channels is always 8

burst periods. Unlike FCCH, SCH contains variable

information which mobile is able to demodulate,

thanks to FCCH.

Contents of SCH burst tells for example, the current

frames index in hyper-frame structure. Like other

broadcast channels, SCH is to DL direction only.

Common Control Channels (CCCH)Paging Channel (PCH) is used to alert the mobile for

incoming calls. Location Area of the mobile is known

by the network at all the times. Typically, location

area contains several cells.

Paging Message is sent on PCH in all the cells

belonging to the location area mobile is known to

reside at the time of incoming call. PCH is to DL

direction only.

Random Access Channel (RACH) is used to ULdirection only by the mobiles to request a dedicated

connection with the BTS, for example when initiating

a call. The name is from the fact that mobiles choose

their emission on the channel randomly.

When connection has been requested by the mobile,

the positive result is reported to DL through Access

Grant Channel (AGCH)

The cell broadcast channel (CBCH) is used to send

short messages from network to mobiles on certain

area. This might be for example traffic information. It

is left to the network operators to define the usage of

this service.

Dedicated Control Channels (DCCH)The stand-alone dedicated control channel (SDCCH)

is used for signalling in call setup. The channel is bi-

directional. It is also used to transfer SMSs when

mobile is on idle mode.

The slow associated control channel (SACCH) is, as

the name reveals, always associated with a TCH. It is

used for signalling purposes during a call, e.g. to send

mobile measurement reports.

SACCH makes a complete cycle (i.e. transmits logically

one whole message) once every four 26 multi-frames.

This corresponds to length 0.48 seconds in time.

Term SACCH Frame refers to one complete SACCH

message sent during the mentioned 0.48 seconds.

Cycle of SACCH is too slow to handle certain

situations, like HOs. Therefore there is a channel used

more rarely (as opposed to SACCH which is used

regularly) when quick signalling is needed.

This channel is called FACCH (Fast Associated Control

Channel). The channel is only used when needed, by

using stealing flags in normal burst structure. This

will result in deterioration of speech quality, since

either or both of the 57 bit information blocks are

used for signalling instead of user data.

From Speech to Radio WavesAnalog speech is converted to digital coding,

protected against transmission errors and

eavesdropping and finally converted back to an

analog radio signal. The steps in the process are

described in the following

Speech DigitalizationSpeech received by the microphone in MS is sampled

at the rate of 8 kHz, corresponding to the resulting bit

rate of 64 kbit/s.


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This data flow is optimized taking advantage of great

redundancy in speech using a method called RPE-LTE

(Regular Pulse Excitation- long term prediction),

resulting in bit flow of 13 kbit/s. without errors in

transmission, the speech quality should be very close

to the one achieved in PSTN at the rate of 64 kbit/s

Channel CodingDue to properties of the radio path the user data flow

has to be protected against transmission errors. This

is channel coding.

User data flow of 13 kbit/s is divided in to blocks of

260 bits, corresponding to time period of 20 ms.

Redundancy is added to each block.

In the case of speech, the 260 bit block is increased in

size to 456 bits, corresponding to gross data flow of

22.8 kbit/s.

This will allow the detection and sometimes

correction of the transmission errors in the receiver.

Each bit is allocated to a certain category according to

its importance for decoded speech quality. Number

bits assigned to each category is presented in the

table below.

The 50 category 1a bits are protected by 3 bit parity

code for error detection. These 53 bits are added

together with 132 category 1b bits.

The result is 185 bit sequence, to which a

convolutional code is applied. It consists of adding 4

tail bits, all being zero, to the end of the sequence and

then applying two convolutions whose polynomials

are D4+D3+1 and D4+D3+D+1.

This results in doubling of 189 input bits. Finally, the

378 protected bits are added with category II bits

which are not protected, leading to 456 bits.

Division of source bits to categories according to

importance

Category 1a 50 bitsCategory 1b 132 bits

Category II 78 bits

Total 260 bits

InterleavingThe convolutional error correction applied to user

data in a receiver is often not able to correct errors

that occur in bursts, i.e. when several consecutive bits

are lost.

Transmission errors in a radio interface tend to

appear in bursts. Therefore a sender interleaves

coded bits before transmitting.

To put it short, interleaving means that logically

consecutive bits are not transmitted next to each

other. In the case of GSM speech interleaving depth is

8, meaning that logically consecutive bits are

transmitted in 8 bit intervals.

Ciphering114 information bits in each burst is encrypted by

performing exclusive-or operation to information bitsand 114 bits long variable key. The key is pseudo-

random sequence established by burst number and

session key.

ModulationThe modulation scheme used in GSM is GMSK

(Gaussian Minimum Shift Keying). Roughly 900 MHz

carrier is modulated by a lower frequency


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information signal. Value of each bit is coded in the

phase of analog radio signal. The modulation scheme

was chosen as a compromise between the spectral

efficiency and the complexity of the demodulation.

From the modulation it follows that channel

separation of 200 kHz between physical channels is

not enough to make adjacent channels non-interfering.

Gross bit rate during burst with chosen modulation is

270.83 kbit/s. when taking into account guard

periods between bursts and the fact that each

physical channel uses only every 8th burst, we end up

to gross bit rate of 22.8 kbit/s per channel as

mentioned earlier.

On radio wave attenuationThe difference between power emitted by the radio

transmitter and the power received by the receiver is

called pathloss.

It is usually expressed in decibels (dB). Decibels

always refer to difference in some power levels; when

one signal power level is referred to, the unit is

decibel meter (dBm).

This means [dBm]-[dBm] = [dB]. Conversion from

milliwatts to dBms is shown later. From the definition

it follows that:

[mW]/[mW] = [dBm]-[dBm]

Pathloss in Free SpaceIn a communication system where receiver and

transmitter are separated by a distance d [m] and

there are no obstructions to signal in between, the

Power Pr at the receiver is given by

Pr (d) = PtGtGr2/(4)2d2LWhere Pt is the transmitted power, Gt is the

transmitted antenna gain, Gr the receiver

antenna gain, is the wavelength in metersand L > 1 is the system loss factor not related

to propagation.

Both Gs and L are dimensionless quantities

and Pr and Pt are in same units.

Interaction of radio waves with physical

objects

When radio wave meets an object which is

much larger in size than the wave length of the

propagating wave, reflection occurs. This

means that part of the energy of the incoming

wave is reflected from the object and part is

penetrated.

The relation between the energy of the

reflected and the penetrated wave depends on

the electric conductivity of material of the

object. Perfect conductor totally reflects theincoming wave.

Diffraction occurs when a wave is obstructed

by an object having sharp irregularities or

edges. The waves bend and can reach behind

of an object, out of line of sight. On

frequencies used by GSM, diffraction depends

on state of the wave (amplitude, phase,

polarization) and the geometry of the object at

the point of interaction.

Multiple objects that are small compared to

the wave length cause scattering in the

propagating wave. Rough surfaces, leaves of

trees, street signs etc. cause scattering in GSM

frequencies.

Interaction of radio waves with objects cause

the pathloss to be proportional to higher power

than -2 as in free space situation in equation

1. In urban environment values from 3.5 to 4

are commonly considered valid. Propagation

models on earth surface are introduced later.

Signal Fading

Deviations of signal strength from its mean is

called fading. When modelling GSM system

two types of fading are usually considered

separately: large scale fading and small scale

fading.

Terms with respect to fading are varying. Some

authors speak about slow (or shadow) fading,

which is due to confusion and should be

included in large scale fading.

Other types of fading are called fast fading orsmall scale fading.

Large scale fading is caused by the movements

of the mobile and its surroundings. Due to

movements, the amount of obstructions

between the mobile and the BTS changes. This

causes the signal strength in receiver to vary

and is called large scale (or slow) fading.

It is often modelled to be log normally

distributed. Large scale fading can be

considered to be constant during one 26

multiframe or even longer, if mobile moves

walking speed.


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There are several reasons to small scale (fast)

fading. The main reason is multipath

propagation of the signal from the BTS to the

MS. Due to varying lengths of distant

propagation paths, components of the original

signal arrive to the receiver in different time

instants. Scattering and reflections also causearriving signal components to vary in phase

and amplitude.

Different propagation paths also cause

different Doppler shifts on each multipath

component. Multipath components are added

according to superposition principle in

receiver.

The result is that a MS experiences potentially

deep (quite often up to 40 dB) fades in signal

strength when it moves in space and time.

Assuming stationary surroundings, the fades

reduce to spatial phenomenon.

Fast moving mobiles suffer less from small

scale fading, since the duration of each fade is

very short and transmission errors during that

interval are probably corrected by the coding

scheme.

Slow moving mobiles may spend time in deep

fade for such a long time that coding is unable

to correct the errors. Typical small scale fading

is presented in the figure below.

Mobile Measurement Reporting

When in dedicated mode (i.e. during a call) a

mobile measures BCCH frequencies defined in

a BA list (BCCH Allocation). Power received on

each frequency is saved and averaged over

several samples taken during one SACCH

Frame.

How many samples are taken depends on thelength of the BA list and is shown in table 3.

When measuring a neighboring cell, mobiles

decodes BSIC (Base Station Identity Code)

from BCCH frequency (this does not always

succeed, which is discussed later).

Actually BCCH frequency (mobile reports index

of BA list, which BSC can convert to BCCH

frequency) and BSIC code are only

identifications available of the identity of the

cell measured by mobile.

The problem is that despite its name, BSIC is

not unique. In fact, there are only six bitsreserved for that, giving 64 distinct BSIC

codes. This leads to the fact that even BCCH-

BSIC combination is not generally unique

identification for a cell in a network.

Recall that transmission of each TRX is

divided into 8 timeslots. Each of these slots is,

independent from others, either transmitting

and receiving (i.e. serving a call) or not.

A BCCH TRX transmits Broadcast information

always on time slot zero. Additionally it can

serve seven calls. However, the BCCH TRX iscontinuously transmitting whether carrying

traffic or not.

If there is no traffic, a dummy signal is

transmitted on each time slot except zero,

which transmits broadcast information.

Moreover, despite the fact that there is a power

control feature that decreases the transmitting

power of both TRXs and mobiles if the quality

of the connection allows it, the transmission

on BCCH TRX is always on full power. This is

to allow the mobiles to perform measurements

on neighboring cells while receiving and

transmitting user information on a busy

schedule.

GSM Network Frequency Planning

Cell Density especially in urban areas has

been increasing with number of subscribers

and services offered in GSM networks.

The planning process is decomposed to 3

independent stages, collecting the data,constructing the interference matrix and

actual frequency assignment.


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Current ways to complete each stage are

studied. The emphasis later in the thesis is on

the first 2 stages of the frequency planning.

Objective of Frequency Planning

With given site locations and frequency bandavailable, the quality of frequency plan greatly

affects the quality and/or capacity of the

network.

Gain from improved frequency plan can be

directed either to increase capacity or to

improve quality of service. Both are needed to

achieve customer satisfaction.

Increase in capacity means tightening

frequency reuse in network and thereby

adding new TRXs to existing cells. This affects

customer satisfaction by reducing call blocking

probability.

Quality improvement means decreasing

interference in radio environment and thereby

decreasing for example number of dropped

calls.

With GSM, as often in other fields of

telecommunications, the issue is to balance

the trade-off between minimizing the costs

while maximizing the quality of service and

capacity.

The objective of frequency planning is to

maximize operator revenue. This might mean

maximizing capacity with chosen lower limit to

quality and given cost (existing sites and

hardware and costs from the planning itself).

It also might mean maximizing quality with a

given capacity. How benefits from improved

frequency planning are directed is up to the

network operator.

Network Quality Indicators

Dropped Call Ratio is the proportion of

successfully initiated calls that are terminated

without user request. It is one of the most

commonly presented single figures

representing an estimation of the quality of

service in an operational network.

This is due to its strong effect on customers;

people expect phones to work and calls

dropping without understandable reasons, like

a railway tunnel, tend to irritate users.

Dropped calls are caused mainly due to lack of

signal strength (coverage), too strong

interference or a hardware fault. Frequency

planning can only reduce number of calls

dropped due to interference.

RXQUAL statistic is an indicator of bit errorrate (BER). BER is approximated by mobile in

a manufacturer specific way, once for every

SACCH Frame (with some exceptions).

Nokia mobiles for example use the following

method: 4 consecutive decoded bursts are

coded. These bits are then compared to the

original coded bits received from radio

interface.

Differing bits divided by total number of bits

gives an approximation of BER. Result is not

accurate since some errors may have remained

uncorrected by the decoding mechanism.

To keep the signalling traffic minimal in air

interface, BER ranging from 0% to 100% is

mapped to RXQUAL ranging from 0 to 7.

Mapping is presented in the table below.

Assumed average BER is directive value to be

used when average BER has to be estimated

based on knowledge of RXQUAL value.

RXLEV is the received power level on a scale of 0 to63. Mobile measures this value from serving cell

frequency and from all frequencies specified in BA

list.

Serving cell RXLEV and up to six highest neighboring

cell power levels are sent over air interface to the

BTS. RXLEV is worse measure for speech quality than

RXQUAL, since received power may be high but still

strongly interfered.

Together with RXQUAL, RXLEV can be used to

determine whether quality is bad due to coverage or

interference problems.

Mapping from RXLEV to dBms can be found below. In

latest specifications (Version 8+) there is also

additional parameter SCALE, which allows mobiles toreport higher than -47 dBm power levels.


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Accuracy in measurements is determined to be at

least +/-4dB when power is in the range from -110

dBm to -70dBm and +/-6dB otherwise.

Stages in FPAfter hardware has been physically installed on sites,

planning the frequencies of large GSM network may

take more than one man year with currently used

methods.

Depending on preferences, the whole process can be

differently divided into more or less independent

stages.

First stage is choosing the source for and collecting

the raw data needed as a basis of planning. Second

step is to construct an interference matrix (IM a.k.a

inter-cell dependency matrix) from the raw data.

Final phase is to actually allocated frequencies to each

cell based on interference matrix and constraints.Depending on selections at each stage, the resulting

frequency plan will induce certain performance in

operational network with new frequency plan.

The constraints affecting the frequency assignment

stage are set by hardware requirements and

potentially other reasons like agreements between

operators near international borders.

Frequency assignment stage is often called, somewhat

misleadingly, automated frequency planning due to

strong contribution of computer algorithms to

frequency assignment.

Collecting the Raw DataHow much does the transmission of one cell affect the

performance of a mobile connected to other?

Currently this question is resolved most by predicting

radio wave propagation.

Since this method is inaccurate, some ad-hoc

measurements from hopefully representative points

of network are used to supplement propagation

predictions.

These methods are currently the only practical

choices to plan a network in roll-out phase. once

network is operational, frequency plan can be

optimized by collecting statistics from the network.

For example, HO statistics can be used for this

purpose.

Propagation PredictionsRadio wave propagation has been widely studied in

literature. There are 3 different propagation model

classes according to COST 231.

One is to theoretically derive a formula based on

knowledge of behavior of electromagnetic waves i.e. a

deterministic model.

The other approach is to do field measurements and

that way establish an empirical model.

Third model class is the combination of the two, a

semi-deterministic model.

Longley-Rice ModelLongley-Rice Model is valid for frequency range from

40 MHz to 100 GHz. It is developed purely on

theoretical basis to be applied to point-to-point

pathloss in irregular non-urban terrain.

Model has been improved several times since its

original publications, for example to better suit urban

terrain as well.

Urban terrain has been taken into account by adding

extra term called urban factor to further increase the

pathloss in urban environment derived from

Okumuras studies.

One shortcoming of the model is for example missing

of multipath propagation.

Okumura ModelOkumura Model is widely used despite of its

relatively old age, although some modifications have

been adopted later, for example in Hat90. Original

model is based purely on extensive measurements in

urban environment in Japan.

Okumura derived set of curves that describe median

attenuation relative to free space pathloss. Model can

be expressed as:

L50 = LF + Amu (f,d) G(hte) GAREA(f)Where L50 is the median value of propagation path

loss in dB, LF is the free space path loss, Amu is the

median attenuation relative to free space attenuation,


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G(hte) is the gain factor from mobile antenna height

and GAREA is the gain from type of the environment.

Set of curves giving Amu (f,d) for frequency and

distance required are listed in Oku68 as well as gain

factors G(hte), G(hre) andGAREA(f)

Okumuras model is performing best on urban and

suburban areas. Standard deviation of the difference

between path loss given by Okumura model and

measurements are around 10 dB to 14 dB. Assuming

normality this would correspond to 95% confidence

interval of roughly +/-20 dB or +/-28 dB.

COST231-Walfisch-IkegamiThis model makes distinction between LOS and NLOS

situations. The model is simple but considered one of

the most accurate ones in urban environment.

It is expressed as:

L = 42.6 +26log(d) +20log(f) for LOS& L = 32.4+20log(d)+20log(f)+Lrts+Lmsd, NLOSWhere L is pathloss in dB, d is distance in km, f

frequency in MHz, Lrts roof top to street diffraction

and scatter pathloss and Lmsd multi-screen diffraction

loss. Lrts and Lmsd are determined by assumed

geometry where uniform height buildings are

between regular interval placed streets.

Manually Measured DataDue to inaccuracies in all radio wave propagation

prediction methods, ad-hoc measurements are

usually used to improve data from predictions. These

measurements are usually performed by surveying

specific part of network with measurement

equipment.

The problem with measurement methods is extensive

data gathering which is very expensive. Furthermore

the effects of cell traffic patterns are not captured by

the method.

Network StatisticsSome statistics stored in OSS can be used to

determine values in IM. The most useful measure is

handover statistics. If two cells overlap, i.e. interfere

with each other, then there will be HOs between the

cells.

The more there is traffic on an overlapping area, the

more there are handovers on average. This allows to

determine numerically the overlap between pair ofcells.

A small trial to examine the correlation between the

number of HO attempts and CCF IM values were

performed. One cell was measured to allow

construction of one row in CCF IM.

Based on this IM row the worst interfering cells for

the measuring cell were ranked. Correspondingranking was also made according to number of

handover attempts during certain time period. For

comparison, the ranking made with NPS/X tool is

listed as well.

Results are presented in table 5. Same data is

depicted in figure 11. Note that in the figure a straight

y=x would represent identical ranking with CCF.

Only 30 first cells according to CCF ranking are

displayed, complete data is presented in Appendix B.

Table 5. Comparison between CCF, NPS/X and HOranking of most interfering cells.

Interferer ranking according to HOs and NPS/Xpredictions against CCF ranking.

In the table above, #NA means that the cell in

question was not defined as a handover candidate,

and therefore no handovers could be made between

the two cells involved.


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There were altogether 29 cells defined as handover

candidates, and every one of those had at least one

handover attempt listed.

Basically frequent occurrence of #NA in HO column

means that HO lists are poorly defined for the cell

measured. But still it can be seen that the correlationbetween CCF ranking and HO ranking is better than

between CCF and NPS/X

When judging the correlation between HO and CCF

ranking it is worth to point out that cells that are on

grey background on table 5 are micro cells. Due to

special HO policy in the network where the data is

taken from, calls are handed over from macrocells

(like the measuring cell) to microcell more easily.

This is shown in data in table 5 because the most

popular HO partner is not so high on CCF ranking

(23rd place).

Different kinds of HO policies are one reason that

decrease the value of HO statistic as a source data for

IM.

However, they have been found to improve

traditional propagation prediction based frequency

plans (as reported by Slovenian operator Mobitel)

Constructing an Interference MatrixWhat is an interference matrix?An interference matrix or inter-cell dependency

matrix (IM) is a matrix that describes the interaction

between cells in a GSM network.

Element (i,j) in the IM somehow describes how BTS i

interacts with BTS j. interaction here means radio

interference if both cells use the same frequency.

In other words, this element describes how well

mobiles in cell i's area receive radio transmission

from BTS j.

Very often physically neighboring cells interact with

each other very much, and are thus transmitting on

different frequencies in a real network.

An example: imagine a network with only 2 BTSs, BTS

A is operating on GSM Frequency 1 and BTS B on GSM

Frequency 6.

These two frequencies are far enough from each

other in the frequency band and can be considered to

be totally non-interfering.

Obviously mobiles attached to A experience nodisturbance what so ever from cell B and vice versa.

Then BTS B is changed to operate on frequency 1 as

well. Element (A,B) in IM should now somehow

describe how much mobiles attached to cell A now

are disturbed or interfered by radio transmissions

from cell B.

IM is a model of real network, and there are countlessways to construct it even if the underlying raw data is

identical. IMs can be divided according to the

meaning of individual elements of the matrix. The

elements might be for example average received

power levels, CIR values, percentage of interfered

traffic and so on.

IM can model either downlink or uplink situation.

Generally GSM network tend to be downlink

interference limited, and therefore downlink matrices

can be considered to be more important.

This is mainly because of use of antenna diversity in

the Base Station (BTS has two receiving antennas,

each time instant signal from the stronger is

selected).

But locally uplink interference may be of importance

too. Element (i,j) in the DL IM describes how mobiles

attached to cell i are interfered by transmission of

BTS j if the two cells are using the same frequency.

Same element in uplink IM quantifies how BTS i

receiving transmissions from mobiles attached to

itself is interfered by mobiles transmitting to BTS j.

As a concluding remark, generally the term

interference matrix can refer to basically almost any

kind of matrix describing either UL or DL interaction

between cells in a network.

However, in this work, the term interference matrix

or IM refers to that particular kind of DL interference

matrix that is achieved when using the method

described later.

Interference Matrix used by NPS/XIn NPS/X each pixel (smallest possible geographicalarea on an electronic map) that is under coverage

belongs to the service area of exactly one cell.

Power received in certain pixel from each BTS can be

calculated. Element (i,j) in interference matrix

describes the percentage of pixels in the service area

of cell i that would experience worse than threshold

C/I value if cell j operates on same frequency with i.

The threshold is given by user. If traffic distribution

inside cell area is estimated by user, it is taken into

account in IM calculation.


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Then the element (i,j) actually estimates percentage

of traffic experiencing worse than threshold CIR.

Channel Separation MatrixChannel Separation Matrix (CSM) contains

constraints on frequency assignment set by hardwarelimitations. Element i,j in CSM is an integer from 0 to

5 and tells the required separation of frequencies

between TRX i and j.

Sometimes CSM is embedded the information from

IM; values from IM can be transferred to frequency

separation requirements.

Frequency assignment can then be made without

actual IM. When wider scale of IM is mapped to

integers from 0 to 5, some accuracy of interference

information is lost.

Allocating FrequenciesFrequency assignment as an optimization problemThe problem of finding an optimal frequency

assignment when interference matrix (cost matrix)

and constraints are known is academically the most

challenging task of the whole frequency planning

process.

Commonly the frequency assignment problem is

formulated to minimize number of frequencies

needed for network with certain traffic while

satisfying constraints given in channel separation

matrix. In this case interference information is

included in CSM.

The approach is somewhat impractical from the

network operator point of view, who has fixed

frequency band available and is only interested in

maximizing capacity or quality in the network.

Size of the FA problemLet us briefly consider what is the size of the FA

problem. For this we use the following notation.

S= number of sites T= number of TRXs

C= number of cells F= number of frequencies

available

Consider a fairly small example network where S=

30, C= 90 (3 cells/site), T=180 (Two TRX per cell)

and F=20.

Then the number of possible assignments N1 when

constraints are not considered is:

N1 = FT = 1.5*10234

When we rule out plans where same frequency is

used twice within any cell, number of possible

assignments N2 is

Similarly forbidding using same channel within one

site reduces number of possible plans to N3

It is obvious that with current computing power,

checking all admissible plans is impossible with small

networks of 90 cells.

Mobile Measurement based FPAdvantages of Mobile Measurement based FP

Traffic Distribution between cells

In a roll-out phase, the amount of traffic to be carried

by each cell is not known. Later when the network is

operational, statistics describing for example average

load on each cell can be collected.

This information can then be used to amend the

original frequency plan.

Improvement is expected, since clearly cells carryingmore traffic have greater need for non-interfered

frequencies.

Assume in network in figure 12, there are 2

frequencies to allocate; clearly cell B should have a

frequency of its own while A and C can share the

same frequency.


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Since mobiles send MMRs during a call in regular

intervals, the total number of MMRs received by any

cell indicates the amount of traffic carried by the cell.

This information is therefore readily available when

constructing interference matrix and the issue needs

not to be considered in FA phase of frequency

planning.

Obviously cell B, carrying average traffic of say, 6

Erlangs benefits more from non interfered BCCH

transmission than cell A, carrying only 3 erlangs,

assuming both cells have only one TRX.

If cell B has 2 TRX and cell A only one, then amount of

traffic carried does not affect the relative importance

of cells A and B.

This is because traffic per TRX is equal in both the

cells.

Traffic distribution inside individual cellWith any prediction based method it is impossible to

know how mobiles move and behave within a service

area of a cell.

Single mobiles can be tracked, but this is not useful as

a source of large scale statistical information.

Traffic distribution within a cell is a factor that affects

the CIR distribution and therefore the call quality in a

cell.

This factor has been neglected traditionally since it is

hard to take into account with prediction methods.

With mobile measurements this issue is however

implicitly taken into account, since the data collected

is dependent on mobile movements and call behavior.

Traffic pattern at each instant is a set of those

physical locations where a call is in progress. This

naturally changes constantly with time in GSM

network as mobiles are not stationary.

However, it is assumed that when traffic pattern is

averaged over sufficiently long time (say a week), it

remains fairly similar.

Power level patterns for each BTS on cell area under

inspection are very complex in urban environment

and impossible to predict accurately.

The fact is that power levels are most interesting

from interference point of view in those locations

where calls are made often.

As a clear example, it does not matter if interference

on most of rooftops would lead to poor quality calls,

since no calls are made there very often.

These kind of things are automatically taken into

account in mobile measurement data. Getting data

with same properties with other methods is

impossible.

Cell Service Areas

Cell service area can be defined in numerous ways.Each has its pros and cons.

Geographical point S belongs to service area of cell A

if and only if the most probable cell acting as server is

A, should a mobile with call ongoing move to S,

initiate or receive a call at S.

Cell service areas depend on several network

parameters. A concrete example of such parameter is

handover power budget margin.

With this parameter, it can be set that a call on macro

layer is handed over to the micro even if power level

on macro is, say 20 dB higher. Obviously changing

this parameter has an effect on cell service areas.

When planning frequencies with propagation

predictions, interference between cells is often based

on estimated cell service areas.

Since predicting cell service areas with radio wave

propagation calculations is very inaccurate, accurate

interference matrix can not be achieved.

Possibility to automate frequency planning procedureThe whole MMFP process can be automated and run

with little work load on an iterative manner.

This offers a possibility to capture the changing

environment in network area.

Radio environment is subject to changes as cells are

being added and new buildings are constructed.

Novel Services offered for mobile phones change the

user behavior.

New coding schemes used set new requirements for

experienced C/I.


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All these changes happen on relatively slow time

cycle, but their long term effect may be significant.

With the frequency planning process automated, the

effect of changes to the network can be captured.

AssumptionsNetwork is DL interference limitedThis assumption is generally accepted for GSM

networks. DL direction is the bottleneck due to better

quality reception in BTS as compared to the mobiles.

Also, looking into the future, different kinds of data

services are becoming more commonly used. For

example, in Internet type of services, mobile would

mostly send short requests to uplink direction and

would then receive larger amount of data to

downlink.

This kind of traffic will furthermore emphasize the

role of DL interference over UL in urban networks.

It is worth noting that network is allowed to be also

so called coverage limited. In this somewhat less

interesting case this method is applicable but just not

as badly needed, since prediction methods and a prior

measurements provide fairly accurate IM.

All DL frequencies of E-GSM propagate similarlyenoughMethod described in this document for creating

interference matrix can only be used to an already

operational network.

Therefore, this network has some frequency

assignment during the time when measurements are

collected.

During measurement period each cell has certain

serving area. Service area here means set of those

physical locations, where call in progress would be

attached to the cell under inspection.

This definition is rather vague, since a cell to which

mobile is attached to is a function of besides

instantaneous received power levels also of history of

power levels and previous serving cell.

This is due to power margins in handover algorithms.

Therefore let us define service area of cell A as set of

those locations, where expected value of serving cell

is A, if there was a mobile with ongoing call on that

particular location.

During measurements each cell has certain servicearea. When measurements are collected, processed

and analyzed and new frequency assignment is made,

each cell that has its frequency changed also has its

service area changed.

This is because of different propagation

characteristics of different radio frequencies.

Measurements and therefore interference matrix andfrequency assignment are based on service areas

before new assignment. Then clearly such assignment

is not optimal if cell service areas are changed.

How much assignment deviates from the optimum

depends on how much cell service areas change.

To get some idea of the magnitude of cell area

changes, the following analysis is made. Let us

assume that the equation below describes radio wave

attenuation sufficiently to our purposes.

L = 40 (1-4x10-3 hb)Log10(R) -18Log10(hb)+21log10(f) +80dB

Where L is the pathloss in dB, h is antenna height in

meters (15 m used here) measured from average roof

top level and f is the frequency in MHz.

The equation above is applicable to urban and

suburban areas where rooftop level is nearly

constant.

Given maximum change in frequency, what is the

corresponding change in distance when pathloss is

kept constant? It can be concluded by applying the

equation above that maximum possible cell service

area change is 4%.

This occurs if cell operates on lowest possible DL

frequency of extended GSM band, 925 MHz and is

allocated new frequency of 960 MHz, maximum

frequency from the same band.

It is worth noting that this is maximum possible

change in cell service area if equation above holds,

and therefore provides worst-case approximation.

In practice no operator has whole GSM900 band in its

use, and of the portion it has, dedicated BCCH band is

only a subset.

In more optimistic case operators BCCH band might

be 5MHz (25 separate GSM frequencies), in which

worst-case area change in cell area is 0.6%.

Considering inaccuracies in cell service area

estimation by radio wave propagation predictions,

these up to 4% changes are negligible.

Inaccuracies in mobiles power measurements have nosignificant impact on IM


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Errors in mobiles power measurements is demanded

to be smaller than +/-6dB when over -70dBm and

+/-4dB otherwise. Received power level is measured

on a scale of 64, so error is allowed to be quite

significant.

Besides random errors there may be, depending onhandset manufacturer, also systematic error sources.

Moreover, during one SACCH multiframe (0.48s)

mobile can only take few samples on each frequency.

There are 96 intervals, during which mobile has time

to measure one frequency .

If length of the BA list is, say 20, that leaves four

samples per each frequency (roughly equal amount of

samples is collected from each frequency)

During SACCH multiframe any signal mobile receives

is considered to be subject nearly to fast fading

(whereas other attenuation factors are considered

nearly constant), so signal strength may be assumed

to approximately follow Rayleigh distribution.

Depending on mobiles speed, it may experience

several fading dips during 0.48s period. On average,

fading dips occur every half wavelength,

corresponding roughly to 17cm with E-GSM

frequencies.

If speed of the mobile is constant 5km/h, easy

calculation shows that it experiences on average 4

fading dips during SACCH.

Due to regular frame structure which allows gaps for

mobile to perform measurements, it is possible that

measurement instants are divided uniformly over

time.

Therefore potentially when frequency 1 is measured,

signal happens to be in fade each time, whereas

frequency 2 happens to be measured outside fading

dips.

This would make frequency 2 appear stronger

relatively to 1 than is really the case. This effect is

shown in figure 13 above.

As a result it can be seen that many factors affect the

results of mobiles power measurement. However,

none of the underlying phenomena is such that itwould appear in one cell but not in other.

Fast fading is present everywhere and random errors

cancel out due to large number of measurements.

Since each cell is likely to contain handsets from

several manufacturers, effect of systematic errors is

also diminished.

Single measured values are not to be trusted. It is still

extremely unlikely that after over hundred thousand

measurements per BTS any cell would gain or lose

anything relative to others when values in

interference matrix are considered.

Construction of an Interference MatrixIM based on Mobile Measurement ReportsAim of an IMInterference matrix is the most important input to

frequency assignment problem. The ultimate aim of

an FA is to find a frequency plan that will maximize

operators revenue.

It is natural to think that this would be equivalent to

maximizing the quality of service experienced by

customers, since capacity is fixed.

Therefore, the purpose of IM is to describe the inter

cell relations in the network in such a manner that FA

algorithm reaches as good frequency plan as possible.

The measure for quality of IMFA is a discrete combinational optimization problem.

It minimizes a cost function while satisfying some

constraints.

The cost function is the result from the IM and the

frequency plan, while the constraints are due to for

example radio equipment limitations.

The exact cost function used varies, but the general

form is as given by 5. An FA alogirthm makes decision

between good and bad frequency plan purely based

on cost function.

It is therefore important that a frequency plan FP1

producing lower cost function value than plan FP2

actually leads to better quality of service in thenetwork.


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This property is depending on the quality of the

underlying IM as well as the cost function chosen.

Weighing IM elements with TrafficAs described earlier, accounting for traffic

distribution at some stage of a frequency plan is veryimportant. There are 2 ways to take into account the

traffic distribution between cells.

An IM can be constructed in such a way that traffic

amounts have no effect on IM elements. This is

feasible if the FA tool used by the network operator

can easily include traffic (weighing factors wi in 5) in

cost function.

On the other hand it is possible that for some

operators gathering traffic data is time consuming or

the FA tool used is unable to include traffic into cost

function. In this case, it is necessary to deliver such an

IM to the FA tool that already implicitly contains

traffic weighing.

When an interference matrix contains traffic within

its elements, it is called traffic weighed IM.

Note that the term traffic weighing here refers to

including inter-cell traffic distribution into IM. Intra-

cell traffic distribution is always implicitly present in

an IM constructed from mobile measurement reports.

Two different ways to obtain IM elements from rawMMR dataFrom information available in the mobile

measurement reports several types of interference

matrices can be constructed. Two general types of

IMs can be distinguished based on the usage of raw

data available from MMRs.

One type is based on power level (or interference, I)

received by mobiles in cell A from each other cell. The

other is based on CIR values.

From historical reasons, the type of IMs taking intoaccount only interference are called CCF IMs (Cell

Coverage Factor)

There are several ways to construct a CCF IM.

Common for all of these is that IM element (i,j) is

somehow derived from the RXLEV distribution

received from cell j by mobiles connected to cell i.

The difference between possible CCF methods is the

exact way how this RXLEV distribution is used to

obtain the final elements.

For example mean value or cumulative sum of thedistribution could be used.

Standard deviation could be included in several ways

and so on. CCF method chosen for implementation by

Nokia is described later on.

Similarly there are several ways to construct an

actual IM based on CIR data. CIR information is

available based on the following.

Each measurement report contains in addition to up

to six neighboring cell power levels also the power

level of the carrier. This allows to calculate

approximate average C/I during the SACCH frame

that the measurement report was sent that would

actually be experienced by mobile if the current

carrier and the reported neighbor would operate on

same frequency.

To clarify this, let us assume the following

measurement report is received.

In example of table 7 only 3 neighboring cells (or

interferers) were reported. None of the neighboring

cells is actually an interferer at the time of

measurements since the cells operate on different

frequencies.

If in new frequency assignment the measuring cell C

is to operate on same frequency with one of the cells,

I1, I2 or I3, that will be the real interferer.

If we assume that cells C and I1 would transmit the

same frequency, then CIR would be -3dB based on the

data in table 7.

Correspondingly for I2 CIR would be 13dB and for I3

21dB. To conclude, in CIR based method instead of

received power levels, the potential CIR values are

stored.

How this CIR distribution is then used to calculate

actual elements in IM can vary.

Interference matrix based on Average powerIn S10 release no CIR information is available from

BSC, and therefore IM is constructed based on

average power level.

Data available and data needed for IM in S10This method is implemented in Nokia S10 system

release. Data flow is illustrated in figure 16. It

represents data (relevant to IM building) coming

from each mobile to BSC.


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Parameter nA in figure 16 is explained later. How BSC

structures the data and sends it forward to OSS is

fixed for S10 release.

In figure 16 this means that the format of the table

between BSC and OSS is non-changeable. Any changes

required can next be implemented at earliest to S11.

On the other hand, the way the OSS builds the IM is

still open due to different phases of BSC and OSS

product lines. The specification is made here.

As can be seen from figure 16, in S10 release BSC

discards information about serving cell received

power level. Therefore complete CIR distribution cant

be used for IM calculation in S10 release.

Three counters giving crude approximation of the CIR

distribution are available, but using average power todescribe interference seems safer approach.

It remains to decide how exactly should the average

power be used to construct the IM elements.

Especially throughout the whole document, term

averaging and summing refers to corresponding

operations being made in linear units as opposed to

logarithmic i.e. all summing and averaging is done in

watts/milliwatts, not in dBms or RXLEVs.

measurement reports based cell planning

Documents