Institutional Repository | Satya Wacana Christian University: Discrete Fourier Transform-Spread Orthogonal Frequency Division Multiplexing pada Jaringan Generasi Keempat (4G)

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67 SIMULASI SC-FDMA

function [SER_ifdma,SER_lfdma] = scfdma(SP)

numSymbols = SP.FFTsize;

Q = numSymbols/SP.inputBlockSize;

H_channel = fft(SP.channel,SP.FFTsize);

for n = 1:length(SP.SNR),

tic;

errCount_ifdma = 0;

errCount_lfdma = 0;

for k = 1:SP.numRun,

% pembentukan simbol masukan (simbol acak) :

tmp = round(rand(2,SP.inputBlockSize));

tmp = tmp*2 - 1;

inputSymbols = (tmp(1,:) + i*tmp(2,:))/sqrt(2);

%%%%%%%%%%%%%

% MODULATOR

%%%%%%%%%%%%%

% proses FFT simbol masukan :

inputSymbols_freq = fft(inputSymbols);

inputSamples_ifdma = zeros(1,numSymbols);

inputSamples_lfdma = zeros(1,numSymbols);

% subcarrier mapping :

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inputSamples_lfdma([1:SP.inputBlockSize]+SP.inputBlockSize*SP.subband) =

inputSymbols_freq;

% proses iFFT :

inputSamples_ifdma = ifft(inputSamples_ifdma);

inputSamples_lfdma = ifft(inputSamples_lfdma);

% proses penambahan CP:

TxSamples_ifdma = [inputSamples_ifdma(numSymbols-SP.CPsize+1:numSymbols)

inputSamples_ifdma];

TxSamples_lfdma = [inputSamples_lfdma(numSymbols-SP.CPsize+1:numSymbols)

inputSamples_lfdma];

% penambahan noise w[n] :

RxSamples_ifdma = filter(SP.channel, 1, TxSamples_ifdma);

% Multipath Channel

RxSamples_lfdma = filter(SP.channel, 1, TxSamples_lfdma);

% Multipath Channel

%%%%%%%%%%%%%

% DEMODULATOR

%%%%%%%%%%%%%

% proses pemisahan CP:

tmp = randn(2, numSymbols+SP.CPsize);

complexNoise = (tmp(1,:) + i*tmp(2,:))/sqrt(2);

noisePower = 10^(-SP.SNR(n)/10);

RxSamples_ifdma = RxSamples_ifdma + sqrt(noisePower/Q)*complexNoise;

RxSamples_lfdma = RxSamples_lfdma + sqrt(noisePower/Q)*complexNoise;

RxSamples_ifdma = RxSamples_ifdma(SP.CPsize+1:numSymbols+SP.CPsize);

RxSamples_lfdma = RxSamples_lfdma(SP.CPsize+1:numSymbols+SP.CPsize);

% proses FFT:

Y_ifdma = fft(RxSamples_ifdma, SP.FFTsize);

Y_lfdma = fft(RxSamples_lfdma, SP.FFTsize);

% subcarrier demapping :

Y_ifdma = Y_ifdma(1+SP.subband:Q:numSymbols);

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H_eff = H_channel(1+SP.subband:Q:numSymbols);

if SP.equalizerType == 'ZERO'

Y_ifdma = Y_ifdma./H_eff;

elseif SP.equalizerType == 'MMSE'

C = conj(H_eff)./(conj(H_eff).*H_eff + 10^(-SP.SNR(n)/10));

Y_ifdma = Y_ifdma.*C;

end

H_eff = H_channel([1:SP.inputBlockSize]+SP.inputBlockSize*SP.subband);

if SP.equalizerType == 'ZERO'

Y_lfdma = Y_lfdma./H_eff;

elseif SP.equalizerType == 'MMSE'

C = conj(H_eff)./(conj(H_eff).*H_eff + 10^(-SP.SNR(n)/10));

Y_lfdma = Y_lfdma.*C;

end

% proses iFFT :

EstSymbols_ifdma = ifft(Y_ifdma);

EstSymbols_lfdma = ifft(Y_lfdma);

EstSymbols_ifdma = sign(real(EstSymbols_ifdma)) + ...

i*sign(imag(EstSymbols_ifdma));

EstSymbols_ifdma = EstSymbols_ifdma/sqrt(2);

EstSymbols_lfdma = sign(real(EstSymbols_lfdma)) + ...

i*sign(imag(EstSymbols_lfdma));

EstSymbols_lfdma = EstSymbols_lfdma/sqrt(2);

I_ifdma = find((inputSymbols-EstSymbols_ifdma) == 0);

errCount_ifdma = errCount_ifdma + (SP.inputBlockSize- ...

length(I_ifdma));

I_lfdma = find((inputSymbols-EstSymbols_lfdma) == 0);

errCount_lfdma = errCount_lfdma + (SP.inputBlockSize- ...

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end

SER_ifdma(n,:) = errCount_ifdma / (SP.inputBlockSize*SP.numRun);

SER_lfdma(n,:) = errCount_lfdma / (SP.inputBlockSize*SP.numRun);

[SP.SNR(n) SER_ifdma(n,:) SER_lfdma(n,:)]

toc

end

function runSimSCFDMA()

SP.FFTsize = 512;

SP.inputBlockSize = 16;

SP.CPsize = 20;

%SP.subband = 15;

SP.subband = 0;

SP.SNR = [0:2:20];

SP.numRun = 10^1;

% TS 25.104

pedAchannel = [1 10^(-9.7/20) 10^(-22.8/20)];

pedAchannel = pedAchannel/sqrt(sum(pedAchannel.^2));

vehAchannel = [1 0 10^(-1/20) 0 10^(-9/20) 10^(-10/20) 0 0 0 10^(-15/20) 0 0 0

10^(-20/20)];

vehAchannel = vehAchannel/sqrt(sum(vehAchannel.^2));

idenChannel = 1;

SP.channel = idenChannel;

%SP.channel = pedAchannel;

%SP.channel = vehAchannel;

SP.equalizerType ='ZERO';

%SP.equalizerType ='MMSE';

[SER_ifdma SER_lfdma] = scfdma(SP);

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SIMULASI PAPR SC-FDMA

function papr_SCFDMA ()

totalSubcarriers = 256; % Jumlah total subcarrier

numSymbols = 64; % Ukuran blok data

Q = totalSubcarriers/numSymbols; % Faktor Penyebaran Bandwidth IFDMA

filterType = 'rr'; % Jenis filter pulse shaping

rolloffFactor = 0.0999999999; % Faktor Rolloff untuk filter raised-cosine

% Untuk mengatasi divide-by-zero, sebagai contoh gunakan 0.099999999

Fs = 5e6; % Bandwidth sistem

Ts = 1/Fs; % Periode Sampling

Nos = 8; % Faktor Oversampling

if filterType == 'rc' % Jika Menggunakan filter Raised-cosine

psFilter = rcPulse(Ts, Nos, rolloffFactor);

elseif filterType == 'rr' % Jika Menggunakan filter Root raised-cosine

psFilter = rrcPulse(Ts, Nos, rolloffFactor);

end

numRuns = 1000; % Jumlah iterasi

papr_ifdma = zeros(1,numRuns); % Inisialisasi nilai PAPR

papr_lfdma = zeros(1,numRuns);

papr_ifdma_PS = zeros(1,numRuns);

papr_lfdma_PS = zeros(1,numRuns);

for n = 1:numRuns,

% Pembentukan data random:

tmp = round(rand(numSymbols,2));

tmp = tmp*2 - 1;

data = (tmp(:,1) + j*tmp(:,2))/sqrt(2);

% Konversi ke ranah frekuensi menggunakan FFT

X = fft(data);

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Yifdma = zeros(totalSubcarriers,1);

Ylfdma = zeros(totalSubcarriers,1);

% Subcarrier mapping

Yifdma(1:Q:totalSubcarriers) = X;

Ylfdma(1:numSymbols) = X;

% Konversi data ke ranah waktu menggunakan iFFT

yifdma = ifft(Yifdma);

ylfdma = ifft(Ylfdma);

% Tanpa pulse shaping

y_result_ifdma = yifdma;

y_result_lfdma = ylfdma;

% Dengan Pulse shaping

% Up-sample simbol-simbol

y_oversampled_ifdma_PS(1:Nos:Nos*totalSubcarriers) = yifdma;

y_oversampled_lfdma_PS(1:Nos:Nos*totalSubcarriers) = ylfdma;

% Lakukan filtering

y_result_ifdma_PS = filter(psFilter, 1, y_oversampled_ifdma_PS);

y_result_lfdma_PS = filter(psFilter, 1, y_oversampled_lfdma_PS);

% Menghitung PAPR:

papr_ifdma(n) = 10*log10(max(abs(y_result_ifdma).^2) / …

mean(abs(y_result_ifdma).^2));

papr_lfdma(n) = 10*log10(max(abs(y_result_lfdma).^2) / …

mean(abs(y_result_lfdma).^2));

papr_ifdma_PS(n) = 10*log10(max(abs(y_result_ifdma_PS).^2) / …

mean(abs(y_result_ifdma_PS).^2));

papr_lfdma_PS(n) = 10*log10(max(abs(y_result_lfdma_PS).^2) / …

mean(abs(y_result_lfdma_PS).^2));

end

% Menggambar CCDF (Complementary Cumulative Distribution Function):

[Ni,Xi] = hist(papr_ifdma, 100);

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[NiPS,XiPS] = hist(papr_ifdma_PS, 100);

[NlPS,XlPS] = hist(papr_lfdma_PS, 100);

figure;

semilogy(Xi,1-cumsum(Ni)/max(cumsum(Ni)),'r')

hold on

semilogy(Xl,1-cumsum(Nl)/max(cumsum(Nl)),'b')

hold on

semilogy(XiPS,1-cumsum(NiPS)/max(cumsum(NiPS)),'r--')

hold on

semilogy(XlPS,1-cumsum(NlPS)/max(cumsum(NlPS)),'b--')

title('CCDF PAPR SC-FDMA menggunakan IFDMA (merah) & LFDMA (biru)');

xlabel('PAPR [dB]');

ylabel('Pr(PAPR>PAPR0)');

grid on;

% Menyimpan data:

save papr_SCFDMA;

function r = rrcPulse(Ts, Nos, alpha)

% Pembentukan Pulse Shaping Root raised-Cosine t1 = [-6*Ts:Ts/Nos:-Ts/Nos];

t2 = [Ts/Nos:Ts/Nos:6*Ts];

r1 = (4*alpha/(pi*sqrt(Ts)))*(cos((1+alpha)*pi*t1/Ts)+(Ts./(4*alpha*t1)).* ... sin((1-alpha)*pi*t1/Ts))./(1-(4*alpha*t1/Ts).^2);

r2 = (4*alpha/(pi*sqrt(Ts)))*(cos((1+alpha)*pi*t2/Ts)+(Ts./(4*alpha*t2)).* ... sin((1-alpha)*pi*t2/Ts))./(1-(4*alpha*t2/Ts).^2);

r = [r1 (4*alpha/(pi*sqrt(Ts))+(1-alpha)/sqrt(Ts)) r2];

function r = rcPulse(Ts, Nos, alpha) % Pembentukan Pulse Shaping Raised-Cosine t1 = [-8*Ts:Ts/Nos:-Ts/Nos];

t2 = [Ts/Nos:Ts/Nos:8*Ts];