MMSE-BASED RECEIVER BEHAVIOUR

IN HANDOVER SITUATIONS

Study of Intercell Interference

João Carlos Silva, Nuno Souto, Francisco Cercas

Instituto Superior Técnico/IT, Torre Norte 11-11, Av. Rovisco Pais 1, 1049-001 Lisboa, Portugal

Rui Dinis

CAPS, Av. Rovisco Pais 1,1049-001 Lisboa, Portugal

Keywords: MMSE Equalizer, handover, MIMO, W-CDMA.

Abstract: This paper focuses on the use of an equalization-based receiver for WCDMA (Wideband Code-Division

Multiple Access) in an inter-cellular environment, for handover studies. The receiver is based on the MMSE

(Minimum Mean Square Error) algorithm and uses the UMTS (Universal Mobile Telecommunications

System) HSDPA (High Speed Downlink Packet Access) standard as a basis, alongside the reference UMTS

environments.

1 INTRODUCTION

In order to cover great areas with coverage for high

data-rate transmissions, several Base Stations (BSs)

need to be employed, with overlapping coverage

areas in order to ensure mobility without dropped

calls. These joint coverage areas are the most

troublesome areas of a cellular system, since it is

where the power levels are lower and where

significant interference from the neighboring cells is

present.

There are many occasions in which the UE (User

Equipment; e.g., mobile phone) is receiving signals

from more than one BS; when in a dense

environment it usually receives signals from a

multitude of BS, though only one or two

“interfering” BSs (Base Stations) usually present a

significant power level. In this study, two setups

were considered, one with two BSs (Figure 1), and

the other with three BSs (Figure 2).

In both setups, two positions were taken as reference.

One where the UE is receiving the same amount of

power from both BSs, and another where the UE is

closer to one of the BSs, thus receiving a higher

power level from the BS it is closer to (it is assumed

that all BSs transmit with the same power level).

Note that power control is not considered since it is

considered that the UE is only dealing with one BS.

Thus, all other Base Stations constitute interference.

For the case where the UE is at point B, it’s

considered that the signal from the closest BS

arrives 3dB higher than the other Base Stations,

whose receive power level is considered to be equal.

In each setup, two cases were considered; one where

the UE knows nothing about the messages from the

interfering BS (Single BS decoding), and the other

were the UE knows the interfering BSs codes, so it

can decode their messages in order to cancel out

their interference (Joint BS decoding). Each BS was

considered to have two transmit antennas, operating

simultaneously, in order to increase the data rate

(spatial multiplexing mode).

Figure 1: Schematic for a 2 BS setup.

171

Carlos Silva J., Souto N., Cercas F. and Dinis R. (2006).

MMSE-BASED RECEIVER BEHAVIOUR IN HANDOVER SITUATIONS - Study of Intercell Interference.

In Proceedings of the International Conference on Wireless Information Networks and Systems, pages 171-176

 SciTePress

Figure 2: Schematic for a 3 BS setup.

Another variable to be considered has to do with

the number of antennas available at the UE. This is

an important issue, since most common UEs usually

have only one antenna (case of normal cellular

phones nowadays), while others may have either two

or more (case of some laptops). The number of

considered receive antennas were one, two and the

total number of transmit antennas (twice the number

of BSs).

As a reference for the current study, the enhanced

HSDPA mode of the UMTS using QPSK modulation

and a SF=16 (Spreading Factor) was chosen as a

reference; a system designed for high data rates. In

order to study the worst case scenario for QPSK, it

was assumed that 6 physical channels (including the

control channel) were transmitting simultaneously.

In order to solve for all messages in an efficient

manner, an equalization based receiver adapted for

multipath MIMO (Multiple Input, Multiple Output)

(Foschini, 1998) is considered for this work, based

on the MMSE algorithm (Latva-aho, 2000).

The structure of the paper is as follows. In section

II, the MMSE receiver for MIMO with multipath is

introduced, and the main results of the inter-cellular

simulations are discussed in section III. The

conclusions are drawn in section IV.

2 LMMSE RECEIVER

A standard model for a DS-CDMA system with K

users (assuming 1 user per physical channel) and L

propagation paths is considered. The modulated

symbols are spread by a Walsh-Hadamard code with

length equal to the Spreading Factor (SF).

Assuming that the transmitted signal on a given

antenna is of the form

()

1,,

() ( )

tx k tx k tx k

ttnT

=−

∑∑

eAbs

, (1)

where N is the number of received symbols,

,ktx k

E=A

, E

is the energy per symbol,

()

ktx

the n-th transmitted data symbol of user k and

transmit antenna tx, s

(t) is the k-th user’s signature

signal (equal for all antennas) and T denotes the

symbol interval.

The received signals of a MIMO system with N

transmit and N

receive antennas, on one of the

receiver’s antennas can be expressed as:

() ()* () ()

tx tx rx

tttt

∑

recn

(2)

where n(t) is a complex zero-mean AWGN

(Additive White Gaussian Noise) with variance

()

,,,

() ( )

tx rx tx rx l l

=−

∑

is the impulse

response of the radio link between the antenna tx and

rx (assumed equal for all users using this link), c

tx,rx,l

is the complex attenuation factor of the l-th path of

the link,

is the propagation delay (assumed equal

for all antennas) and * denotes convolution. The

received signal on can also be expressed as:

()

,, ,

1 111

() () ( ) ()

NKL

k tx k tx tx rx k l

ntxk l

tttnTt

= ===

=−−+

∑∑∑∑

rx=1

rAbcsn

(3)

Using matrix algebra, the received signal can be

represented as

+rSCAbn

, (4)

where S, C and A are the spreading, channel and

amplitude matrices respectively. The structure of the

matrices is explained in detail in (Silva, 2005).

Vector b represents the information symbols. It has

length

(

)

KN N

⋅

, and has the following

structure

TX TX TX

1,1,1 N ,1,1 1,K,1 N ,K,1 N ,K,N

=b ,,b ,,b ,,b ,,b

⎡

⎤

⎣

⎦

……… …b

.(5)

Note that the bits of each transmit antenna are

grouped together in the first level, and the bits of

other interferers in the second level. This is to

guarantee that the resulting matrix to be inverted has

all its non-zeros values as close to the diagonal as

possible. Also note that there is usually a higher

correlation between bits from different antennas

using the same spreading code, than between bits

with different spreading codes.

The n vector is a

(

)

XRXMAX

NSFN N

⋅⋅ + ⋅

vector

with noise components to be added to the received

vector r

, which is partitioned by N

antennas,

1,1,1 1, ,1 ,1,1 , ,1 ,1, , ,

=,,,,,, ,, ,,

MAX RX MAX RX

vSFNNSFNNNSFN

ψψ

⎡

⎤

⎣

⎦

……… … …rr r r r r r

(6)

Equalization-based receivers compensate for all

effects that the symbols are subject to in the

transmission chain, namely the MAI (Multiple

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172

Access Interference), ISI (Inter-Symbolic

Interference) and the channel effect. Thus being,

only the thermal noise cannot be compensated for,

since only its power level can be effectively

estimated.

The equalization receiver used as basis in this works

makes use of the MMSE algorithm, as is based on

the Matched Filter output,

()

SCA r

(7)

The MMSE estimate aims to minimize

⎛⎞

−

⎜⎟

⎝⎠

, where

M , MMSE

= R + σ

I (8)

R = A

⋅ C

⋅ S

⋅ S ⋅ C ⋅ A (9)

The MMSE estimate is thus

(

)

MSE M MMSE MF

−

=yE y

, (10)

with

(

)

−

=⋅+

SCA R I

. (11)

3 RESULTS

All results are portrayed in BER versus received

. In the case of simulations for point B, results

are portrayed against the received E

value of the

closest BS. Four different channels were simulated;

one with 6 equal fingers/taps, the flat fading channel

(1 finger), the Vehicular A and the Pedestrian A

channel models referenced for the UMTS (3GPP,

2003). For the simulations performed in position A,

the BER of the “Best” BS was also shown. This

BER is indicative of the system’s performance if a

scheme similar to STD was to be employed. What

was considered in the simulation was simply to

account the errors of the BS with the least amount of

errors for each simulated block – this provides an

important performance bound.

For the simulations using position B, the BER of the

high power (closest) BS was analyzed, alongside the

BER of the low power (one of the farthest) BS.

Therefore, it’s possible to obtain some precious

conclusions from both cases of position B, especially

for handover situations.

Results - UE in point A – Single BS Decoding

For Position A with single BS detection, only for the

case where the UE has 2 or more receive antennas

(Figure 4 and Figure 5), there are some good results

for the case of only one interfering BS, contrary to

the case in Figure 3. When using 2xBS receive

antennas, all results are satisfactory (close to 10

-2

Note also that the channels with the largest spread (6

finger and Vehicular A channels) yield the worse

results when a small numbers of antennas is used at

the receiver, and yield the best results when the full

number of antennas are employed (2xBS), due to the

added capability of the antennas sorting out the

different multipath components, and exploiting them

for added diversity gains

Figure 3: BER performance for the best BS in position A

using a single BS decoding philosophy and 1 receive

antenna.

Figure 4: BER performance for the best BS in position A

using a single BS decoding philosophy and 2 receive

antennas.

MMSE-BASED RECEIVER BEHAVIOUR IN HANDOVER SITUATIONS - Study of Intercell Interference

173

Figure 5: BER performance for a fixed BS in position A

using a single BS decoding philosophy and 2xBS receive

antennas.

Results - UE in point A – Joint BS Decoding

When using joint decoding (Figure 6 and Figure 7),

the UEs with one receive antenna only present

satisfactory results (in this case, a BER value lower

than 10

-1

for an Eb/N0 of 20dB) when there is only

one interfering BS. UEs with a higher number of

receive antennas perform well under all scenarios.

Note also that when using joint-decoding of the BSs,

the dispersive channels present the best results, due

to the exploitation of multipaths.

Figure 6: BER performance for position A using a joint

BS decoding philosophy and 1 receive antenna.

Figure 7: BER performance for position A using a joint

BS decoding philosophy and 2 receive antennas.

Results - UE in point B – Single BS Decoding

For position B with single BS detection, using one

receive antenna (Figure 8) is only somewhat

acceptable (BER of 10

-1

) in the presence of 2 BS,

and when the UE is using the closer BS. For the case

of using the farthest BS, BER levels of 10

-1

and

lower are only possible with 2xBS antennas (Figure

9).

Figure 8: BER performance for position B using a single

BS decoding philosophy and 1 receive antenna; results for

decoding the high power BS.

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Figure 9: BER performance for position B using a single

BS decoding philosophy and 2xBS receive antennas;

results for decoding the low power BS.

Results - UE in point B – Joint BS Decoding

When using joint detection, the UE with 1 receive

antenna (Figure 10) performs acceptably when there

is only one interfering BS (2 Base Stations), and the

UE is farther from this interferer (high power BS);

however, when another interferer is introduced (3

Base Stations), the performance degradation is very

significant

Figure 10: BER performance for position B using a joint

BS decoding philosophy and 1 receive antenna; results for

decoding the high power BS.

With a higher number of receive antennas (2 and

2xBS antennas for Figure 11 and Figure 12

respectively), all cases provide good results (BER of

-2

and lower).

Figure 11: BER performance for position B using a joint

BS decoding philosophy and 2 receive antennas; results

for decoding the low power BS.

Figure 12: BER performance for position B using a joint

BS decoding philosophy and 2xBS receive antennas;

results for decoding the low power BS.

4 CONCLUSIONS

In summary, when using single BS decoding and

when there is a significant amount of interference

from other BSs, 1 receive antenna at the UE simply

does not work. However, with the use of 2 or more

receive antennas, and ultimately with the aid of the

codes from the other BSs in order to cancel their

interference effect as much as possible, best results

can be obtained in the presence of significant

interference. What this means, in terms of handover,

is that a soft handover is required between cells,

especially for the case of UEs with a small number

of receive antennas, using the HSDPA protocol.

Hard handovers should only be allowed when the

receiver is able to cope with the adverse conditions

of the interfering cells when at the transitional zone

MMSE-BASED RECEIVER BEHAVIOUR IN HANDOVER SITUATIONS - Study of Intercell Interference

175

ACKNOWLEDGEMENTS

This work has been partially funded by the C-

MOBILE (Advanced MBMS for the Future Mobile

World) project, and by a grant of the Portuguese

Science and Technology Foundation (FCT)

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pp. 311–335, Mar. 1998.

M. Latva-aho, M. Juntti, "LMMSE Detection for DS-

CDMA Systems in Fading Channels", IEEE

Transactions on Communications, vol.48, no2,

February 2000.

J. Silva, N. Souto, A. Rodrigues, A. Correia, F. Cercas, R.

Dinis, “A L-MMSE DS-CDMA Detector for

MIMO/BLAST Systems with Frequency Selective

Fading”, accepted in IST Mobile&Wireless

Communications Summit 2005, Dresden, Germany,

19.23 June 2005

S. Kay, “Fundamentals of Statistical Signal Processing:

Estimation Theory”, Englewood Cliffs, NJ: Prentice-

Hall, 1993, pg391

3GPP Technical Report 25.996 v6.1.0 (2003-09).

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