Interference Mitigating Waveform Design for Next Generation Wireless Systems

Organised by the Institution of

Engineering and Technology

Radar, Sonar and Navigation Network

TheKnowledgeNetwork

Keynote Address:

Interference

-

Mitigating

Signalling Waveform

Design

for Wireless Systems

Professor

Lajos Hanzo,

Southampton

University,

UK

Southampton

University

Printed and

published by

the

IET,

Michael

Faraday

House,

Six Hills

Way,

About the Speaker

Professor Hanzo is a Fellow of the Royal Academy of

Engineering, who received his first-class

degree

in

electronics in 1976

and his doctorate in 1983. In 2004 he was awarded the Doctor of

Sciences

(DSc)

degree

by

the

University

of

Southampton,

UK.

During his career in

telecommunications

he has held various research and academic posts in

Hungary,

Germany and the UK. Since 1986 he has been with the

Department of Electronics and

Computer

Science,

University of Southampton, UK,

where he holds the

chair

in

telecommunications.

He

co-authored

14

books

totalling

10

000

pages on

mobile radio

communications,

published

in excess

of 650

research

papers,

organised and chaired conferences,

presented various keynote

and overview lectures and has been awarded a number of distinctions.

Currently

he directs the

research

of

a

50-strong academic team,

working

on

a

range of research

projects in the field of wireless multimedia communications

sponsored

by industry, the

Engineering and

Physical

Sciences

Research

Council

(EPSRC) UK,

the

European IST Programme

and the Mobile

Virtual

Centre

of

Excellence

(VCE),

UK. He is an

enthusiastic supporter

of

Interference-Mitigating

Waveform

Design for Next-Generation Wireless

Systems

A

Light-hearted Keynote Address

L.

Hanzol

School of ECS,

Univ.

of

Southampton, SO17 1BJ, UK.

Tel:

+44-(0)23-8059-3125,

Fax:

+44-(0)23-8059-4508

Email:

[email protected]

http://www-mobile.ecs.soton.ac.uk

ABSTRACT

A briefhistorical perspective of the evolution of waveform

de-signs employed in consecutive generations of wireless communi-cationssystemsisprovided, highlighting therangeof often

con-flicting demandson thevariouswaveform characteristics. Asthe culmination ofrecentadvances inthefieldthe underlying bene-fitsof variousMultiple Input Multiple Output (MIMO) schemes

arehighlighted and

exemplified.

As an integral part of the

ap-propriate waveform design, cognizance is giventotheparticular choice of theduplexing scheme used for supporting full-duplex communicationsand itis demonstrated that Time Division

Du-plexing (TDD) is substantially outperformed by Frequency Divi-sionDuplexing (FDD),unlessthe TDD scheme iscombinedwith

further sophisticatedscheduling, MIMOs and/or adaptive

mod-ulation/coding. Itis also argued thatthe specific choice of the Direct-Sequence (DS) spreading codes invoked in DS-CDMA

pre-determinestheproperties of the system.Itis demonstratedthat a

specifically designed family of spreading codes exhibitsaso-called interference-free window (IFW)and hencethe resultant systemis

capable ofoutperforming its standardised counterpart

employ-ingclassic OrthogonalVariableSpreadingFactor (OVSF) codes

under realisticdispersive channel conditions, provided that the

interfering multi-user and multipath components arrive within

this IFW. Thiscondition may be ensured with the aid of

quasi-synchronousadaptive timingadvancecontrol.However, a

limita-tionof thesystemisthatthe number ofspreadingcodesexhibiting

acertainIFWislimited, although this problemmaybemitigated with the aid ofnovel code design principles, employing a

com-bination of several

spreading

sequences in the time- frequency-and

spatial-domain.

Thepaper is concluded by

quantifying

the

achievable userload ofaUTRA-like TDD Code Division

Multi-pleAccess(CDMA) systememploying Loosely Synchronized (LS)

spreading codes

exhibiting

an IFW in

comparison

tothatofits

counterpartusing OVSF codes. Both

system's

performance

is

en-hancedusing beamforming MIMOs.

Thefinancial supportof theEPSRC,UKandtheEU intheframework

of theNEWCOM, NEXWAYandPHOENIXprojects isgratefully

acknowl-edged. Theauthor wouldalso liketoacknowledgethe contributions of his closecolleaguesandprofessional friendsandtoexpress hisgratitudeforthe

enlightenment gainedfrom thecollaborations withthose, whose work was

cited in thereferencesection.

IETWaveformdiversityanddesign incommunications,radar,sonar

andnavigation,22nd ofNovember,2006, Savouy Place,London,UK

Implementational

complexity

Channel

Coding/interleaving

characteristics

delay

System

_Modulation

Codinig

Bit error_rate

bandwidth

sh

EffectiveCoigan

throughput

TCodinggain

Coding rate

Figure 1: Factors affecting the design of wireless signalling wave-forms

[1].

1. HISTORIC EVOLUTION OF WAVEFORM-DESIGNIN

WIRELESSCOMMUNICATIONS

1.1. TheEarly Years

Theefficient designofwireless signalling waveformshas to take into account the entire host ofcontradictory design trade-offs portrayed

in Figure 1, as it will be detailed in this treatise. Historically speak-ing,thefirst-generation wireless systems were mainly based on ana-logue Frequency-Modulation

(FM).

although their control channels

have useddigital signalling.

During

the 1980s substantial research

efforts were invested in designingthe first digital mobileradio

sys-tem.

which - for the first time - supported international roaming in theheartof Europe [2].

During

theperiodleadingto the

standardisa-tion of thePan-EuropeanGSMsystem[2]numerousnovel

waveform-designconcepts wereinvestigated. Theinvestigationsconsidered var-ious spectrally efficient modulation schemes

requiring

highlylinear

amplification [3]aswell aspartial-response GaussianMinimum Shift

Keying(GMSK) [2]. Partial-responseGMSK uses aso-called Gaus-sian filter for spreading the effects of a single modulating bit over three consecutive bitintervalsand hencedeliberatelyintrQduces

Inter-Symbol

Interference

(1SI),

which in tumrequiresachannelequaliser

atthe receiver fordetectingeach bitevenintheabsence of channel-induceddispersion [2]. In exchange for the

equaliser's

extra

complex-itythe GMSK-modulated waveformexhibitsasnarrow aspectrum,as

possible, since theGaussian pulsehas thenarrowest

possible

band-widthowingtoits smoothestpossibletime-domain waveform

non-linearamplification and hence can be amplified using power-efficient class-C amplifiers, which results in a low power-consumption by the handset.

AlthoughGSM has become the most prevalentsecond-generation

(2G) standard right across the globe, there were a numberof other 2G

standards. Forexample, thePan-American IS-54 system [2] and the

JapaneseDigital Cellular(JDC) systems optedfor using

w/4-rotated

Quadrature Phase Shift Keying (QPSK) constellations for

transmit-ting2bits/symbolatthe costofrequiring somewhat higher received

Signal-to-Interference-Plus-Noise Ratios (SINR) than GMSK.

Fur-thermore,QPSK requires linear class-A power-amplification or

am-plifier linearisation techniques [3], which is substantiallyless

power-efficientthanthenon-linear class-C poweramplifiersreadily tolerated

by the constant-envelope GMSKsignal.

By the early 1980s the understanding of waveform design has

reached a certain maturity andresearchers embarked on

investigat-ing alternative, more 'exotic' modulated waveform shapes. such as

the employment of both DirectSequenceCodeDivisionMultiple

Ac-cess (DS-CDMA) [4], as well as Frequency-Hopping (FH) assisted CDMA

[4].

The great significance ofthese studies wasthat for the first time, researchers were closely following the Shannonian

prin-ciples of rendering both the modulated DS-CDMA signal as well

as the Co-channel Interference (CCI) noise-like in statistical terms, since bothDS-spreading aswell asFH broaden the transmitted sig-nal'sspectrum, hencerendering themsimilartothe spectrumof noise.

Although spread-spectrum principles were also considered for

em-ployment inthe GSM system in the early 1980s, they have lost out

topartial-response GMSKwave-form design. Further

developments

inthe state-of-the-art ofweaveformdesign for CDMA systems

fol-lowed,when the first so-calledM-ary orthogonalCDMA systemwas

proposed byQualcom fortheir 2G system

[2]

inthe early 1 990s. By thetime thestandardisation of the

third-generation (3G)

sys-temsgatheredmomentum

during

the 1990s

[4],

the

understanding

of

waveformdesignfor diverse CDMA systems reacheda stateof

matu-rity, including thedesignof various

DS-spreading

waveforms

[4].

In addition to the transmission of classic voice

signals [5],

there wasa

commercial demand formore

bandwidth-hungry

applications,

suchas

thetransmission of both still and interactive video

signals

[6].

which stimulatedfurther research for the sake ofsupporting both variable-rateandhigh-ratewireless Internetservices. Both the Europeanand

Japanese 3G solutions

[7]

opted for the employment of wideband

DS-CDMA using achip-rateof 3.84MChips/s in anapproximately

5MHz

bandwidth andOrthogonalVariableSpreadingFactor(OVSF)

DS

spreading

waveforms using Walsh-Hadamard (WH)codes. By

contrast, the Pan-American cdma2000

system

invoked three

paral-lel subcarriers. leading to the conception of the first commercially

available Multi-Carrier DS-CDMA (MC-DS-CDMA) system. using

aMC-waveformdesign[4].

In the mean-time Moore's law andarange of other advances in

technology, suchasthe designof

high-linearity

poweramplifiers fa-cilitated theemployment of higher symbol rates and the transmission

ofmulti-bit Quadrature Amplitude Modulation (QAM) signals

[3].

As a natural counter-measure against the violently fluctuating Sig-nal toInterference plus Noise-Ratio(SINR), the philosophy of

near-instantaneously Adaptive QAM (AQAM) or Burst-by-Burst Adap-tive (BbBA) QAM was proposed. which was documented in detail in[4,8]. These waveform design advance have led to the conception ofthe High-Speed

Downlink

Packed Access (HSDPA) High-Speed

UplinkPacked Access

(HSUPA)

modes of the 3G

systems,

which rely

onthe extensice employment of AQAM and adaptive channel coding

concepts [1]. Naturally,the transceivers have to be designed tosatisfy the exactspecifications of the highest-throughput and hence most sen-sitiveQAM mode of operation. Clearly,thisambitious waveform

de-signphilosophy hasmoved way beyond therobust constant-envelope waveform design philosophy of class-C non-linear amplification

em-ployedin theGSM system.

It isimperative thatthewaveform design developments of both Digital Audio Broadcast (DAB) [8] and Digital Video Broadcast(DVB) [6]systems as well asthose of the family of Wireless Local Area Net-works (WLANs) are also portrayed. In both of these categories multi-carriertransmission techniquesbased onOrthogonal Frequency Divi-sionMultiplexing (OFDM) havefoundfavour

[9].

Although OFDM techniques

[9]

exhibit numerous benefits in terms of

implementation-ally efficient modulation, demodulationaswell asequalisation

tech-niques, they areeven moresensitive toamplifier non-linearities than theirsingle-carrier QAMcounterparts[3]. Similarproblemsarealso encounteredby their closerelatives, namely by thefamilyofvarious

MC-CDMA schemes, although boththe so-called

peak-to-average-power-ratio(PAPR)and theresilienceof the systemsubstantially

de-pendsonthespecific choice of DSspreading factors, asdetailedin

Chapters9 and 11 of

[9].

Nonetheless, atthe current state-of-the-art

itappears likely that thenext-generation wireless systems will

em-ployhighly flexible, reconfigurableBbB AQAM-aidedmulti-carrrier

transmissiontechniquesowingtotheirhigh flexibilityintermsof

pro-vidingarangeof bitrates andtransmissionintegrities.

Itis worthnotingatthis stagethat most of the above-mentioned research efforts have beeninvested in

designing

bandwidth-efficient

modulated waveforms. which are beneficial in noise-limited, rather than interference-limited environments, i.e. in single-user scenar-ios. Furthermore.whenthe transmitter inflictsnon-lineardistortions, while thechannelimposeslinear distortions,onlysophisticated chan-nel equalisers and multi-user equalisers are capable of attaining a

near-single-user performance. However. the complexity of Multi-User Detectors (MUDs) [4] is typically high. since their effective channelmatrixcontainsthe convolution of the DSspreadingsequences with the CIR and thispotentially largematrix may havetobeinverted,

unlessalternative

reduced-complexity techniques

are

employed.

Hence inrecentyears the concept ofcombinedTime-Domain

(TD),

Frequency-Domain(FD) andSpatial-Domain (SD) spreading emergedas an

at-tractive low-complexity alternative, as argued in

[4].

For example,

usingalowspreading factorof SF=8 in all three domains would al-lo", us to support a total of

83=5l2

usersby separating them in the TD. FD and SD.respectively.

1.2. The MIMO Era

In recent years various smart antennadesignshave emerged. which

have foundapplication in diverse scenarios, as summarised in

Ta-ble I. Themainobjectiveofemploying MIMOs isthat ofcombating

the effects ofmultipath fading on the desired signal and

suppress-ing interferingsignals,thereby increasing both the performance and

capacityof wirelesssystems. Toelaborate a little further, insmart

an-tennaassistedsystemsmultiple antennas may be invoked both at the transmitterand/orthereceiver, where the antennas may be arranged forachieving spatial diversity,directionalbeamforming or for

el-Space Division Mul- SDMsystems also employ multiple antennas, but in contrast to SDMA arrangements, notfor the sake of

tiplexing (SDM) Sys- supporting multiple users. Instead, they aim forincreasing thethroughput ofa wireless system in terms

tems[10] ofthe number of bits per symbol that can be transmitted by a given user in agivenbandwidthat agiven

integrity.

Space Division Multi- SDMA exploits theunique, user-specific "spatial signature" of the individual users for differentiating

ple Access (SDMA)[9] amongst them. This allowsthe system to support multiple users within the same frequency band and/or

time slot.

Spatial Diver- In contrast to the A/2-spaced phased array elements, inspatial diversityschemes,suchasspace-timeblock sity (STBC [11], ortrelliscodes

[lI]

themultipleantennas arepositionedasfar apart aspossible,sothat thetransmittedsignals STTC [ 12]) [ 1] and ofthedifferentantennasexperienceindependentfading, resulting in the maximumachievablediversity gain.

Space-Time Spreading

(STS) [4]

Beamforming[7] Typically A/2-spaced antenna elements are used forthe sake of creating a spatially selective

transmit-ter/receiver beam. Smart antennas using beamforming have been employedformitigatingthe effects of

cochannel interferingsignalsand forproviding beamforminggain.

Table 1: The four mainapplicationsof MIMOs in wirelesscommunications

11

10 Nt=Nr=2

9.,

4-2>

-10 10

SNR(C

1

Diversity

... -* Multiplexing

AWGN - -- Rayleigh

20 30

JB)

Figure 2: The capacity of the MIMO uncorrelatedRayleigh-fading

channel and AWGN channel for classic two-dimensional 16QAM

(Al = 16. D 2) and for so-called four-dimensional orthogonal

signalling (.Al 32. D = 4), when usingNt = Nr = 2transmit

and receiveantennas: Ng& Hanzo. [13].

ements, whereit isunlikely forseveral antennaelementsto simulta-neously experienceahigh attenuation. This independent fading

phe-nomenon typically results in a beneficial diversity gain. Naturally.

theachievable performance improvements of MIMOs are afunction

ofthe antenna spacing and that of the algorithms invoked for

pro-cessing the signals received by theantennaelements, which will be

exemplified during our further discourse in thecontext ofthe four

main MIMOtypes summarised in Table 1. Asanexample. in Fig-ure 2 Nt = Nr = 2 antennas wereused and both so-calledclassic

16QAM andmoreunorthodox, buthigher-capacity four-dimensional

signalling wasused[13] for the sake ofquantifyingtheir maximum

achievable performance benefits. The MIMO schemes of Table 1

were designed for achieving various design goals. The Spatial

Di-visionMultiplexing [10, 14] (SDM) schemes aim for maximisingthe

attainable multiplexing gain,i.e. thethroughputofagivenuser. By

contrast, Space DivisionMultipleAccess(SDMA)arrangements [9] maximisethe number ofuserssupported. Alternatively, attainingthe

maximumpossible diversity gain is theobjective of the plethoraof

space-timeblockcoding [11]aswellasspace-timetrelliscoding [12]

schemes found in theliterature [1]. Finally, beamforming mitigates

theeffectsof interferingusers roamingin the vicinity of the desired user[7],providedthattheyareangularlyseparable.

Here wecontinueourdiscoursebyprovidingasuccinctexample

of theabove-mentionedfour MIMO subclasses of Table 1 and briefly

characterise their attainable performancein Figures 3-6. More

specif-ically.

in Figure 3 the BERversus SNR performance of the

sphere-decodingaided and MIMO-assisted SDM OFDM receiver of

Chap-ter 10 is

characterised.

whichexhibits a near-Maximum Likelihood

(ML)performanceat arelatively lowcomplexityin high-throughput scenarios using

Nt

= Nr = 6 transmit and receiveantennas and

64QAM. The rank-deficient scenario- namely when we have more

transmit antennas thanreceiveantennas-usingNtxNr=6x4 16QAM

MIMO-OFDMalsoperformsadequately,when theOFDM

subcarri-ersexperience independent flat fading. Thethroughput of these sys-temsis 36and 24bits/symbol, respectively.

Remarkably.

the

36-bit-throughput6x6-dimensional64QAM system outperforms the

24-bit-throughput 6x4-dimensional 16QAMsystem, as a benefit of using a totalof 6x6=36antenna elementsinsteadof24,which provides a sub-stantialdiversitygain in addition to the SDM gain.

Let us nowbriefly consider Figure

4.

where instead of the SDM scheme ofFigure3supportingasingle user, an SDMA system

allocat-ingthe increasedthroughput of theMIMO-OFDM system to several

users wascharacterised. Afurtherattractivefeature of this system is that insteadof the turbo channel codec of Figure

3.

a

sophisticated.

iteratively detectedjoint coding and modulation scheme was

used.

whichisreferredto asTurbo Trellis Coded Modulation

(TTCM)

[1].

Finally,in contrast to the near-ML sphere-decoder of Figure 3 [14],

theIterativeGeneticAlgorithm (IGA)aided Minimum Mean Squared

Error(MMSE) multiuser detector was employed. Hence wetermed

thissystem as theTTCM-MMSE-IGA-SDMA-OFDM

arrangement.

The novelIGA-aidedtechniqueemployedthenovel BiasedQ-function

BasedMutation (BQM) techniqueproposed in [15] for the sake of

approachingtheperformanceof the ML detectoratthe cost of a

sub-stantially lowercomplexity. Observe in the figure thatbothperfect

andimperfectchannel estimationscenarioswere considered and that

the number ofusers wasL= 6 - 8, whilethe number of SDMA

re-ceiver antenna elements wasP=6. SimilarlytotheSDM system of

Figure3,this SDMAarrangement is alsocapableofoperatingin high-throughput rank-deficient scenarios.

Having consideredboth the SDM and SDMAsystems of Table1,

let usnowbrieflyexemplifya

cutting-edge

transmit

diversity

scheme

in Figure 5. Explicitly, Alamouti's STBC schemewas further

de-0

E

.0

TTCM-MMSE-IGA-SDMA-OFDM, Lx/P6, 4QAM, SWATM

lo

Lli

20

Figure 3:BERversusSNRperformanceofthesphere-decodingaided

andMIMO-assistedSDM OFDM receiverofChapter10(Akhtman

& Hanzoin [14]. which exhibitsanear-Maximum Likelihood(ML)

performanceandarelatively lowcomplexity inhigh-throughput

sce-narios using Nt = Nr = 6 transmit and receive antennas and

64QAMas wellas for the rank-deficientscenariousing NtxNr=6x4

1 6QAMMIMO-OFDM.The OFDMsubcarriers experience

indepen-dentflatfading. Thethroughputis 36 and 24bits/symbol, respec-tivel,y.

velopedbyjointly, ratherthan separately desiging the two transmit antenna's andtwotimeslots' signalswith the aid ofSpherePacking (SP)modulationusingiterativedetection,asdetailed in[16. 17]. It is

worth noting,however that channel estimation isanextremely

com-plex processin thecontext of MIMOs. since inthe exampleof

Fig-ure3atotal of 36channels hastobeestimated. In orderto circum-vent this problem. in [18] the philosophy of differentially encoded STS(DSTS)wasproposed. Inthiscontextitwasalsodiscussed that

the mapping of the bits tothe SP modulation scheme is highly

in-fluentialintermsofdeterminingthe overall systemperformance and

that the classic Graymappingisoftenoutperformedbyvarious map-pers,which donotabeytheGar-mappingrules andhencearetermed

asAnti-Gray Mapping (AGM)schemes. Finally observe inFigure 5

that theemploymentofaunity-rateprecoder[ 18] hasthe potential of substantially improving the iteratrively decoded system's attainable

performance.

Thetourthdominant member of thefamilyofMIMOs summarised

inTableI isconstituted bybeamforming. InFigure 6anoveliterative

detection aided beamformer is characterised. This scheme is more

radical than the classic MMSEbeamformerweight adjustment

tech-nique. since it directly minimises the BER. ratherthan the MMSE.

as detailed in [20, 21. 22, 23. 24, 25, 26] in thecontext of various

wirelesssystems. Observe inFigure6 thatasthenumber ofdetection

iterations is increased, the BERperformance approaches that ofthe

single-userscenario,despite operatinginthehighlydemanding rank-deficient scenario ofsupportingsixuserswith the aid oftwoantenna

elements, where allchannels are assumed to benon-dispersive and

independently fading. Moreexplicitly,this powefulsystemis capable

ofsupportinga three times higheruserload than thenumber of

an-tennaelements, while the conventional rule ofthumb is thatonly as

manyusersmaybesupportedasthenumberof receiverantennas.

Let us now briefly summarise our previous discussions, before

4 .S

EW,/N) (dB)

Figure 4: BER versus

Eb/

o performance comparison of the

TTCM-assisted MMSE-IGA-SDMA-OFDM system using BQM,

while employinga4QAMscheme for transmissionovertheSWATM

channel, where L=6, 7, 8 users are supported with the aid of P=6

receiverantenna elements, respectively. The simulation parameters

usedaregiven in Table 2(®)Jiang&Hanzo of[15].

proceeding further. Following decades ofwaveform design efforts.

BbBAQAMmulti-carrier transceiversusingvarious MIMOtechniques havereached astateofmaturity andare likelytofind theirwayinto

thetool-box ofthenext-generation wirelesscommunicationsenabling techniques. In the rest of this light-hearted overview wewill focus

ourattentiononanattractive subclass ofbeamformingaidedCDMA

systems using specifically designed interference-immune spreading

sequences. inordertocharacterise the totalnetwork-layerbenefitsof

thephysical-layerperformanceimprovements reported.

2. LOOSELY SYNCHRONISED SPREADINGSEQUENCES

Inourpreviousresearch[71. wequantifiedthe UTRA FDDsystem's

performance using both adaptivebeamforming andadaptive

modu-lation. The system employed OVSF spreading codes, which offer the benefit ofperfect orthogonality in an ideal channel. Hencein a non-dispersive channel, all intracell users' signals are perfectly

or-thogonal. However,uponpropagatingthroughadispersivemultipath

channelthisorthogonalityiseroded. hence all otheruserswill

inter-fere with the desireduser'ssignal. Thereforeinpracticetheintra-cell

interference is alwaysnon-zero, when using OVSF codes for

trans-missionoverdispersive channels.

Theabove-mentionederosion ofcode orthogonalitymaybe

mit-igated with the aid ofLoosely Synchronized (LS) spreading codes [4,

28. 29. 30].These codes exhibitaso-calledInterferenceFreeWindow

(IFW),wheretheoff-peak aperiodic autocorrelation valuesaswellas

theaperiodic cross-correlation valuesbecomezero,resultingin zero

ISI andzeroMAI, provided that the delayed asynchronous

transmis-sions arrive withinthe code's IFW. More specifically,

interference-Table 2: Arrivalanglesoftheusers' signals

userk 1 2 3 4 5 6

k'

i15°

-4° 36° -240 68° -480

o sdm-cmp-16qam:27-Jun-2005

10

10-1

10-2

3

LU1o

0-5

~.. ...

* SOPHIE- _.. _

*MMSE- -A

16QAM 4 0

_ 64QAM6 4

0-6 L

5 10

Eb/No[dB] 15

I~~~~

-T

0o-4

DSTS, (4Tx,1Rx),

fD=0.01

I

lo-l1

10-2

310

10-4 10

lo-6

4 5 6 7 8 9

Eb/No[dB]

I-10

10 11 12

-C

.0

Figure 5: Near-capacity performance of an Anti-Gray Mapping

(AGM) based convolutional-coded Differential Space-Time Spread

& Sphere-Packed (DSTS-SP) schemes inconjuction with L =

16-arySPmodulation, while using noprecoding together with the

sys-tem employing a unitary-rate precoder and Gray Mapping (GM),

while using aninterleaver length of D = 1,000, 000 bits, I 10

iterations®El-Hajjar.Alamri, Ng & Hanzo [19]. 10°

Singleuser

Noiteration X Iteration #1

3K

Iteration#5 S

Iteration#10

Iteration#15

Iteration

Iteration#25

: --Iteration #27

c: - '-* -Iteration#30

mi

-v Iteration #35

10-3

2.4 2.6 2.8 3 3.2

Eb/No (dB)

Figure 6: BER performance of the iterative MBERbeamforming

re-ceiver of OTan, Chen & Hanzo [27] using a two-element antenna

arrayforsupportingK= 6usershaving the angles of arrival listedin Table 2 andexperiencing uncorrelated Rayleigh fading for all chan-nels.

free CDMA communications become possible even without a

mul-tiuser detector, when the total time offset expressed in terms of the

number ofchipintervals, which isthe sumofthe time-offset of the

mobiles plus the maximum channel-induced delay spread is within

thecode's IFW[31]. Byemployingthisspecific familyofcodes,we arecapable of reducingboth the ISI and theMAI,sinceusersin the samecelldonotinterferencewitheachother,asabenefit of theIFW

provided bythe LS codes used.

There exists aspecific family ofLS codes [32], which exhibits anIFW,whereboth theauto-correlationandcross-correlationof the

codes becomezero. Specifically, LScodes exploittheproperties of

the so-calledorthogonal complementarysets[32]. Anexampleof the

o 10

2 L)

I00

Table 3: Simulationparameters.

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0

MeanCarried Teletraffic

(Erlangs/km2/MHz)

4.5

Figure 7: Forced termination probability versus meancarried traffic

of theUTRA-like TDDcellular network using LS codes and OVSF

codes both withaswell aswithoutbeamformingin conjunction with

shadowing having afrequencyof 0.5 Hz andastandard deviationof

3dBforaspreading factor of SF=16

(©)Ni,

Wei& Hanzo [35]

design ofLS spreading codescanbe found in[33]. Inthese

investiga-tionsthecell-radiuswassetto78m,whichwasthemaximum afford-able cell radius for the IFWduration of ±1chip intervals at achip

rateof 3.84Mchip/s. Alternatively, the adaptive timingadvance

con-trolhastomaintainamaximumdelay difference ofonechip-duration,

sothattheinterferingcomponentsarrive within this IFW. The mobiles wereroamingfreely,atapedestrian speed of 3mph. in random direc-tions, selectedatthestartof thesimulationfrom auniform

distribu-tion, withinthe infinite simulationareaof 49wrapped-around traffic

cells [7]. Furthermore, the post-despreading Signal to Interference

plusNoise Ratios(SINRs) requiredforobtaining thetargetBit Error Rates(BERs)weredetermined with the aid ofphysical-layer

simula-tionsusinga4QAMmodulationscheme,inconjunctionwith 1/2-rate

turbocoding for transmissionover aCOST 207seven-pathBadUrban (BU)channel [34]. Usingthisturbo-coded transceiver and LS codes

havingaSF of 16,thepost-despreading SINRrequiredfor maintain-ing the target BER of x

10-3

was 6.2dB.The BER, whichwas

deemedtocorrespondtolow-quality communicationswasstipulated

at5 x 10-3 ThisBER wasexceeded forSINRsfalling below 5.2

dB. Furthermore,alow-quality outagewasdeclared, when the BER

of x 10-2 wasexceeded,whichwasencountered for SINRs below

4.8 dB. These valuescanbeseenalongwith the othersystem param-etersinTable 3. All otherexperimental conditions wereidenticalto

thosein[7].

Parameter Value

Cell radius 78 m

Signalbandwidth 5MHz

Modulationscheme 4QAM/QPSK

Spreading

factor 16

Max BSMS TX power 17dBm

MinBS MS TX power -44dBm

Pedestrian speed 3mph

-Nobeamformin- O OVSFCodes

9-element beamformin 3 LSCodes

-elementbeamrormini_c~~~~~~~~~~0

0

I 0

OVSFCodes°

0 i

LSCodes

10

4 6 10 12

Mean Cam'ed Teletraffic(Erlangs/km-/MHz)

achieved

by employing

LScodescomparedtothescenariousing OVSF

codes.

Specifically,

the networkcapacitywaslimitedto 152users,or

to ateletraffic load of approximately 2.65 Erlangs/km2/MHz. With

the adventofemploying four-element adaptive antenna arrays [7]at

the base stationsthe number of users supported by the network

in-creasedto428 users, oralmostto7.23 Erlangs/km2/MHz.

However,

inconjunction with LS codes, and evenwithout employingantenna

arrays atthebase stations the networkcapacity wasdramatically

in-creasedto581 users,or10.10Erlangs/km2/ MHz. When the

four-elementadaptive antenna array was employedinthe LS code aided

scenario, the systemwascapableofsupporting800users, which

cor-respondedto ateletraffic load of 13.39Erlang/km2/MHz. This is be-causethe LS codes' auto-correlation and cross-correlationfunctions

exhibit an

IFW.

which essentiallv eliminated the intra-cell

interfer-14

ence.

Figure 8: Forced termination probability versus meancarriedtraffic

oftheUTRA-like FDD cellular network using LS codes and OVSF

codes both withaswellaswithoutbeamforminginconjunction with shadowing having afrequency of 0.5 Hz andastandarddeviation of 3dBforaspreading factor of SF= 16 ©Ni, Wei & Hanzo [35]

3. FDD VERSUS TDD NETWORK PERFORMANCE UNING LS

CODES[351

The BERperformance of OVSF codes and LS codeswascompared[29],

which wasdetermined with the aidofphysical-layersimulations

us-ing a4-QAM modulation scheme. 1/2-rate turbocoding anda

Mini-mumMeanSquared Error Block Decision Feedback Equalizer

(MMSE-BDFE) based Multi-User Detector (MUD) for transmission over a

COST 207 seven-path Bad Urban channel. The achievable BER

per-formanceofLScodesisbetter than that of OVSF codes. Fora spread-ing factor of 16. thepost-despreadingSINRrequired formaintaining aBER of1 x

10-3

was6.2dB incaseof LScodes, whichisalmost

2dBlower than that necessitatedbytheOVSF codes. Figure7shows

the UTRA-like TDD/CDMA system's forced termination

probabil-ity associated with a variety oftraffic loads quantified in terms of

themean normalized carried traffic expressed in Erlangs/km2/MHz,

whensubjectedto0.5 Hzfrequency shadowinghavingastandard

de-viation of 3 dB. As observed in thefigure, nearlyanorderof

magni-tude reduction oftheforced terminationprobability has been achieved

by employing LS spreading codes comparedtothose ofusing OVSF

spreading codes. Inconjunction with OVSF codes, the "No beam-forming"scenariosufferedfromthehighest forced termination prob-ability of the four traffic scenarios characterized in the figureatagiven load. Specifically. the networkcapacitywaslimitedto50users. orto

a teletraffic density ofapproximately 0.55 Erlangs/km2/MHz. With

theadvent ofemploying 4-element adaptiveantennaarrays [7]atthe base stations the number ofuserssupportedby theTDDsystem in-creasedto 178users, ortoateletraffic density of2.03Erlangs/km2

MHz. However, in conjunction with LS codes, and even without

employing antenna arraysatthe base stations, theTDDsystemwas

capable ofsupporting 306 users, or an equivalenttraffic density of

3.45Erlangs/km2/MHz.

Figure 8 portrays the UTRA-like FDD/CDMA system's forced

termination probability versus various traffic loads. The figure

il-lustrates that the network's performance wassignificantly improved

by using LS codes. As observed in the figure, nearly an order of

magnitude forced termination probability (PFT) reduction has been

4. SUMMARYANDCONCLUSIONS

A briefhistorical

portrayal

of the evolution of waveformdesign for

wirelesscommunicationswasprovided.Thiswasfollowedbya

rudi-mentary overviewof the fourmostprevalentMIMOs summarised in Table 1leach of whichwasexemplified andbriefly characterisedin Figures3-6.Finally,asacompletesystemdesign study,the network

performanceof aUTRA-like systememploying LSspreading codes was shown to be substantially better than that of the system

using

OVSF codes. In the context ofthe interference limited 3G CDMA

system LS codes might hold the promise of an increased network

capacity without dramatic changes of the 3G standards. However,

LS codes exhibittwo

impediments.

Firstly,the number of

spreading

codes

exhibiting

acertain IFW islimited and hence underhigh user-loads thesystemmaybecomecode-limited,rather than

interference-limited. The number ofLS codes may beincreasedusingthe

pro-cedureproposedin [36]. butfurther research is required for increas-ing the number of codes. A particularly attractive solution is to

in-vokeboth DS-CDMA time-domain(TD)andfrequency-domain

(FD)

spreading[37]tomultiplecarriers inMC-CDMA.Thiscanbeachieved for example usingLS and OVSF codes inthe TD and FD,

respec-tively. Thennomultiuser detection(MUD)isrequiredinthe TD and

the MUDemployed in the FD hasalow complexity owingtousing

anOVSF codehavingalow SF. The total number ofusers

supported

becomestheproductofthe number of LS and OVSF codes.

The seconddeficiency of LS codes is that they tendtoexhibita short IFWduration. However, thisdeficiencyis also eliminatedwith

the aid of the above-mentioned joint TD and FD spreading regime.

because upon spreading the informationtomultiple carriers the TD

chip-duration may be commensurately extended by a factor corre-spondingtothenumber of carriers.

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