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ThequalityforspreadingspectrumofDSSS:

✧Anti-interference

✧Multipleaddress

CDMA（CodeDivisionMultipleAddress）:

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

✧CodeDivisionMultipleAddressSystemcanberealizedbytakingadvantageoftheorthognalityofthePNsequence.

●BasicRequirement

Inthisexperiment,thefollowingitemsneedtobedone:

✧Writeaprogramtogeneratethemsequencewith

[000010101000101]

✧Drawtheautocorrelationofthegeneratedm-sequence

✧Buildupasimulationsystemofthegivenfigurewiththedatarate1bit/s,spreadinggain64andthecarrierfrequency128Hz.

●ExperimentProcedure

Ø

Thecodeforgeneratingthem-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

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

✧Drawtheautocorrelationofthegeneratedm-sequence

Thefollowingcodeisusedtomanipulatethecorrelationoftwosignals:

functionr=coorr（seq1,seq2）

◆ifnargin==1

◆seq2==seq1;

◆N=length（seq1）;

◆fork=-N+1:

-1

◆seq2_shift=[seq2（k+N+1:

N）seq2（1:

k+N）];

◆r（N+k）=seq1*seq2_shift'

;

◆fork=0:

N-1

◆seq2_shift=[seq2（k+1:

k）];

Inputthefollowingcode,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'

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

◆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

sumLength%setsamplingfrequencytobe

◆%fs=128*8=1024Hzi.e.8sample/T

◆data（（1+（i-1）*1024）:

i*1024）=cdmData（i）;

%fs/f=1024samples

◆%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

PNlength

◆PNcode（（1+（i-1）*16）:

i*16）=x_code（i）;

%16samplesperPNcode

◆%thenwegenerateasequenceofPNcodewiththelength64*20*16=

◆%length（d）

3.SpectrumSpreading

◆fmodSig=data.*PNcode;

%PNcode:

frequencyspreadingcode

◆%fmodSig:

frequencymodulatedsignalbyPNcode

4.BPSKModulation

◆%carrierfrequency:

128Hzcosinsignal

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;

◆%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））;

◆%EsNodB=4;

◆%sigma=sqrt（10.^（-EsNodB/10）/2）;

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

5.BPSKdemodulation

%8samplesperCarrierPeriod

◆demodSig（（1+（i-1）*8）:

i*8）=modSigWithNoise（（1+（i-1）*8）:

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

●Conclusion

✧Throughthesimulationofsystemwithandwithoutnoise,withandwithoutspreadingspectrum,wecanseethatiftheEs/Noisequal,thebiterrorrateofthesystemwithspreadingspectrumisbetterthantheonewithoutspreadingspectrum.

✧DSSShashighqualityofanti-interference.

✧TheDSsignalhasverywidespectrum,asmallfractionoffadingcouldnotinfluencemuchforthewholesignal.

✧DSSShasgoodabilityofmultipleaddressing.