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扩频通信流程matlab仿真

●Backgroundknowledge

SpreadSpectrum:

Formtheformular

wecanseethattoobtainasamecapacity,wecanincrease

✧

todecreasetherequiredbandwidthandthereforeimprovethespectralefficiency.

✧BandwidthBtodecreasetherequired

.Moreover,wemaydecreasethe

tosuchalowlevelthatthesignalpowerisunderthenoisepowerlevel,thisiscalledSpreadSpectrumModulation.

Theprincipleofspreadspectrum:

✧Inthesenderside,theinformationismodulatedintodigitalsignal,thenthePNcodeisusedtomodulatethedigitalsignalsothatthespectrumofthesignalisspreaded,finallythespreadedsignalissentout.

✧Inthereceiverside,weusethesamePNcodetode-spreadthesignal,andrecovertheoriginalinformation.

✧Aboveall,wecanfindoutforageneralSpreadSpectrumCommunicationSystem,thereneedsthreetimesofmodulationandcorrespondingdemodulation.Theyareinformationmodulation.SpreadspectrummodulationandRadioFrequencymodulation.

DSSS（DirectSequenceSpreadSpectrum）:

TherearedifferentkindsoftechniquesaboutSpreadSpectrum,herewemainlylookattheDirectSequenceSpreadSpectrum（DSSS）:

✧ForDSSS,weusuallyuseperiodicalpseudosequence（PNsequence）tomodulatethebasebandsignals,andexploitthemodulatedsignaltocontrolthephaseofcarrierwave.

✧ThefollowingistheDSSSsystem,andthepseudorandomsequencegeneratorgeneratesthespreadingsequence:

✧Thefollowingisthespectraofdesiredreceivedsignalwithinterference:

（a）widebandfilteroutputand（b）correlateoutputafterde-spreading

Thecorrelationofthespreadspectrumcodesequence:

✧ThePNcodecanbeapproximatelyregardedasrandomsignal,soitsharessomeprosperitiesofnoise.

✧WechoosePNcode,thatisbecauseintheprocessofinformationtransformationthelargerthedifferencebetweendifferentsignalsthebettertransformationquality.Thisqualitycanberepresentedintheformofautocorrelation.

ThequalityforspreadingspectrumofDSSS:

✧Anti-interference

✧Multipleaddress

CDMA（CodeDivisionMultipleAddress）:

✧BecauseoftheadvantagesofDSSS,suchastheanti-jammingcapability,lowprobabilityofinterception,multipleaccesscapabilityandsoon,ithasbeenwidelyappliedforsecurecommunicationsandmobilecommunicationsknownasCodeDivisionMultipleAccessSystem.

✧CodeDivisionMultipleAddressSystemcanberealizedbytakingadvantageoftheorthognalityofthePNsequence.

●BasicRequirement

Inthisexperiment,thefollowingitemsneedtobedone:

✧Writeaprogramtogeneratethemsequencewith

[000010101000101]

✧Drawtheautocorrelationofthegeneratedm-sequence

✧Buildupasimulationsystemofthegivenfigurewiththedatarate1bit/s,spreadinggain64andthecarrierfrequency128Hz.

●ExperimentProcedure

✧Writeaprogramtogeneratethemsequencewith

ØThecodeforgeneratingthem-sequenceisasfollowing:

◆function[mseq]=mseries（coefficients）;

◆len=length（coefficients）;

◆L=2^len-1;%thelengthoftheshiftregister

◆registers=[zeros（1,len-1）,1];

◆%theinitialcontentoftheshiftregister

◆mseq

（1）=registers（len）;

◆fori=2:

L

◆newregisters

（1）=mod（sum（coefficients.*registers）,2）;

◆forj=2:

len,

◆newregisters（j）=registers（j-1）;

◆end;

◆registers=newregisters;

◆mseq（i）=registers（len）;

◆end

Øwesavethispieceofcodeasafunction,thentypestem（mseries（[000010101000101]））andwegetthefollwoinggraph:

✧Drawtheautocorrelationofthegeneratedm-sequence

ØThefollowingcodeisusedtomanipulatethecorrelationoftwosignals:

functionr=coorr（seq1,seq2）

◆ifnargin==1

◆seq2==seq1;

◆end

◆N=length（seq1）;

◆fork=-N+1:

-1

◆seq2_shift=[seq2（k+N+1:

N）seq2（1:

k+N）];

◆r（N+k）=seq1*seq2_shift';

◆end

◆fork=0:

N-1

◆seq2_shift=[seq2（k+1:

N）seq2（1:

k）];

◆r（N+k）=seq1*seq2_shift';

◆end

ØInputthefollowingcode,thenwecangetthefollowinggraph:

◆mseq=[000010101000101];

◆ind1=find（mseq==0）;

◆mseq（ind1）=-1;

◆r1=coorr（mseq,mseq）;

◆N=length（mseq）;

◆axis=-N+1:

N-1;

◆plot（axis,r1）

◆xlabel（'k'）;

◆ylabel（'R（k）'）;

◆title（'TheautocorrelationofM-sequence'）;

✧Buildupasimulationsystemofthegivenfigurewiththedatarate1bit/s,spreadinggain64andthecarrierfrequency128Hz.

1.Generationoftheoriginaldata:

◆%SYSTEMREQUIRMENTS

◆%databitrate:

1bit/s

◆%carrierfrequency:

128Hz

◆%spreadgain:

64

◆clc;clearall;closeall;

◆%Firstofallweneedtogeneratetheoriginaldata

◆%byusingRandn（）function,standardnormaldistribution

◆%andwesettheoriginaldatatobeof1'sand-1's

◆data_length=20;%sdefinethelengthofeachuser'soriginaldata

◆numOfUser=4;%specifythenumberoftheusers

◆sumLength=numOfUser*data_length;%theoveralldatalengthis20*4

◆d=zeros（numOfUser,data_length）;%4*20doublematrixofallzeros

◆randn（'state',sum（100*clock））;%maketheseedofthefunctiondifferenteachtime

◆fori=1:

numOfUser

◆d（i,:

）=sign（randn（1,data_length））;%1*20doublematrix

◆end

◆dd=[d（1,:

）;d（2,:

）;d（3,:

）;d（4,:

）]';%20*4doublematrix

◆%Generatetheorthorgnal4orderedWalshcode

◆%Where4representthenumberofusers

◆walshCode=hadamard（numOfUser）;%callthefunctionhadamard（）,walshCodeis4*4matrix

◆walshCode=walshCode/2;%normalisitionwis

◆s=dd*walshCode;%Coding:

ddisofthesize20*4;walshCodeisofthesize4*4

◆%sisofthesize20*4

◆cdmData=reshape（s',1,4*data_length）;%cdmData'ssize:

1*80

◆fori=1:

sumLength%setsamplingfrequencytobe

◆%fs=128*8=1024Hzi.e.8sample/T

◆data（（1+（i-1）*1024）:

i*1024）=cdmData（i）;%fs/f=1024samples

◆end

◆%ENDofstep1.Wehavegeneratedtheoriginaldatasequencedoflength

◆%equalsto20*numOfUser*1024=81920

2.GeneratethePNsequence

◆g=41889;%G=1010001110100001b14=b13*b9*b8*b7*b5*b0

◆state=16385;%state=10000000000000114‘0'afterthefirst'1'

◆PNlength=64*sumLength;%PNfrequencyis64Hz,64Hz/1Hz=64.

◆x_code=sign（mgen（g,state,PNlength）-0.5）;%turn-1's&1's

◆fori=1:

PNlength

◆PNcode（（1+（i-1）*16）:

i*16）=x_code（i）;%16samplesperPNcode

◆end

◆%thenwegenerateasequenceofPNcodewiththelength64*20*16=

◆%length（d）

3.SpectrumSpreading

◆fmodSig=data.*PNcode;%PNcode:

frequencyspreadingcode

◆%fmodSig:

frequencymodulatedsignalbyPNcode

4.BPSKModulation

◆%carrierfrequency:

128Hzcosinsignal

◆fori=1:

length（data）/8

◆AI=1;%theamplitudeofthecarriersignal

◆dt=2/3;

◆n=0:

dt/7:

dt;%8samplesperPeriodofCarrier

◆cI=AI*cos（2*pi*n*1.5）;

◆modSig（（1+（i-1）*8）:

i*8）=fmodSig（（1+（i-1）*8）:

i*8）.*cI;

◆end

◆%AddingNoise

◆%AWGNchanneladdingnoisetothesignal

◆EsNodB=0:

8;

◆sigma=zeros（1,length（EsNodB））;

◆fork=1:

length（EsNodB）

◆sigma（k）=sqrt（10.^（-EsNodB（k）/10）/2）;

◆modSigWithNoise=modSig+sigma（k）*randn（1,length（modSig））;

◆end

◆%EsNodB=4;

◆%sigma=sqrt（10.^（-EsNodB/10）/2）;

◆%modSigWithNoise=modSig+sigma*randn（1,length（modSig））;

5.BPSKdemodulation

◆AI=1;

◆dt=2/3;

◆n=0:

dt/7:

dt;%8samplesperCarrierPeriod

◆cI=AI*cos（2*pi*n*1.5）;

◆fori=1:

length（data）/8

◆demodSig（（1+（i-1）*8）:

i*8）=modSigWithNoise（（1+（i-1）*8）:

i*8）.*cI;

◆end

6.Frequencydemodulation

◆fdemodSig=demodSig.*PNcode;

7.Receiveddata

◆RecovData=zeros（1,length（fdemodSig））;

◆value=zeros（1,length（fdemodSig）/1024）;

◆avg=zeros（1,length（fdemodSig）/1024）;

◆forj=1:

（length（fdemodSig）/1024）

◆avg（j）=2*sum（fdemodSig（1+（j-1）*1024:

j*1024））/1024;

◆%*****!

!

!

!

!

integralofsinorcosfunctionneeda

◆%multiplicationof2

◆value（j）=round（avg（j））;

◆RecovData（1+（j-1）*1024:

j*1024）=value（j）;

◆End

8.Makejudgments.

◆%.Demultiplexing

◆v=reshape（value,4,20）;%4*20

◆rd=v'*walshCode;%20*4matrix

◆rd=rd';%4*20matrix

9.Calculatetheerrorrateofthewholeprocess

◆error=sum（sum（abs（v-s'）/2））;

◆errorRate=100*error/sumLength;

◆disp（'Theerrorrateofthisprocessis:

'）;

◆disp（errorRate）;

10.Demultiplexing

◆%.Demultiplexing

◆v=reshape（value,4,20）;%4*20

◆rd=v'*walshCode;%20*4matrix

◆rd=rd';%4*20matrix

●Conclusion

✧Throughthesimulationofsystemwithandwithoutnoise,withandwithoutspreadingspectrum,wecanseethatiftheEs/Noisequal,thebiterrorrateofthesystemwithspreadingspectrumisbetterthantheonewithoutspreadingspectrum.

✧DSSShashighqualityofanti-interference.

✧TheDSsignalhasverywidespectrum,asmallfractionoffadingcouldnotinfluencemuchforthewholesignal.

✧DSSShasgoodabilityofmultipleaddressing.