vec xcorr(const vec &x, const vec &y, const int max_lag, const std::string scaleopt)
{
cvec out(2*x.length() - 1); //Initial size does ont matter, it will get adjusted
xcorr(to_cvec(x), to_cvec(y), out, max_lag, scaleopt, false);
return real(out);
}
vec spectrum(const vec &v, const vec &w, int noverlap)
{
int nfft = w.size();
it_assert_debug(pow2i(levels2bits(nfft)) == nfft,
"The window size must be a power of two in spectrum()!");
vec P(nfft / 2 + 1), wd(nfft);
P = 0.0;
double w_energy = energy(w);
if (nfft > v.size()) {
P = sqr(abs(fft(to_cvec(elem_mult(zero_pad(v, nfft), w)))(0, nfft / 2)));
P /= w_energy;
}
else {
int k = (v.size() - noverlap) / (nfft - noverlap), idx = 0;
for (int i = 0; i < k; i++) {
wd = elem_mult(v(idx, idx + nfft - 1), w);
P += sqr(abs(fft(to_cvec(wd))(0, nfft / 2)));
idx += nfft - noverlap;
}
P /= k * w_energy;
}
P.set_size(nfft / 2 + 1, true);
return P;
}
void xcorr(const vec &x, const vec &y, vec &out, const int max_lag, const std::string scaleopt)
{
cvec xx = to_cvec(x);
cvec yy = to_cvec(y);
cvec oo = to_cvec(out);
xcorr(xx, yy, oo, max_lag, scaleopt, false);
out = real(oo);
}
// }}}
itpp::Mat<std::complex<double> > RandomGUE(int const dim, std::string normalization="sigma_offdiag=1", double const percentage_away=0.1){ //{{{
if (normalization=="sigma_offdiag=1"){
return RandomGUEDeltaOne(dim);
}
else if (normalization=="unfolded mean_level_spacing=1"){
itpp::Mat<std::complex<double> > U(dim, dim), tmp(dim,dim);
itpp::Vec<std::complex<double> > vec1(dim);
itpp::Vec<double> eigenvalues(dim);
FlatSpectrumGUE(U, eigenvalues);
for (int i=0; i<dim; i++){
vec1=itpp::elem_mult(conj(U.get_col(i)), to_cvec(eigenvalues));
for (int j=i; j<dim; j++){
tmp(i,j)=vec1*U.get_col(j);
if (i<j){tmp(j,i)=conj(tmp(i,j));}
}
}
return tmp;
// std::cout << eigenvalues << std::endl ;
// ya dentro de temp tenemos a una matriz que no esta
// unfolded. tengo que encontrar los eigenvectores,
// luego los eigenvalores, eso diagonalizarlos y chan
} else {
std::cerr << "Illegal normalization RandomGUE" << percentage_away;
exit(1);
}
// Aca poner un factor de normalizacion opcional
}
cvec polyval(const cvec &p, const vec &x)
{
it_error_if(p.size() == 0, "polyval: size of polynomial is zero");
it_error_if(x.size() == 0, "polyval: size of input value vector is zero");
cvec out(x.size());
out = p(0);
for (int i = 1; i < p.size(); i++)
out = std::complex<double>(p(i)) + elem_mult(to_cvec(x), out);
return out;
}
CORASMA_BER_Test::CORASMA_BER_Test()
{
modem=new Modem_CORASMA();
int L=1;
int OF=1;
cmat fading;
cvec channel1,channel2,channel3,channel4,channel5,channel6,channel7,channel8,channel9,channel10,channel11,channel12,channel13,channel14,channel15,channel16;
bvec transmitted_bits;
bvec received_bits;
cvec sum_chips;
cvec transmitted_symbols;
cvec received_chips;
double norm_fading;
BERC berc,berc1,berc2;
AWGN_Channel channel;
vec EbN0dB = linspace(1000, 1000, 1);
vec EbN0 = pow(10, EbN0dB / 10);
double Eb = 1.0;
vec N0 = Eb * pow(EbN0, -1.0);
int NumOfBits = modem->nb_bits;
int MaxIterations = 10;
int MaxNrOfErrors = 200;
int MinNrOfErrors = 5;
vec ber;
ber.set_size(EbN0dB.size(), false);
ber.clear();
RNG_randomize();
for (int i=0;i<EbN0dB.length();i++){
cout << endl << "Simulating point nr " << i + 1 << endl;
berc.clear();
berc1.clear();
berc2.clear();
channel.set_noise(N0(i));
for (int j=0;j<MaxIterations;j++) {
transmitted_bits = randb(NumOfBits);
sum_chips=modem->modulate(transmitted_bits);
transmitted_symbols.set_length(sum_chips.length()+L+1);
transmitted_symbols.zeros();
fading.set_size(L,sum_chips.length());
fading.zeros();
channel1.set_length(sum_chips.length());
/* channel2.set_length(sum_chips.length());
channel3.set_length(sum_chips.length());
channel4.set_length(sum_chips.length());
channel5.set_length(sum_chips.length());
channel6.set_length(sum_chips.length());
channel7.set_length(sum_chips.length());
channel8.set_length(sum_chips.length());
channel9.set_length(sum_chips.length());
channel10.set_length(sum_chips.length());
channel11.set_length(sum_chips.length());
channel12.set_length(sum_chips.length());
channel13.set_length(sum_chips.length());
channel14.set_length(sum_chips.length());
channel15.set_length(sum_chips.length());
channel16.set_length(sum_chips.length());*/
for(int k=0;k<sum_chips.length()/OF;k++){
channel1.replace_mid(k*OF,ones_c(OF));
/* channel1.replace_mid(k*OF,randn_c()*ones(OF));
channel2.replace_mid(k*OF,randn_c()*ones(OF));
channel3.replace_mid(k*OF,randn_c()*ones(OF));
channel4.replace_mid(k*OF,randn_c()*ones(OF));
channel5.replace_mid(k*OF,randn_c()*ones(OF));
channel6.replace_mid(k*OF,randn_c()*ones(OF));
channel7.replace_mid(k*OF,randn_c()*ones(OF));
channel8.replace_mid(k*OF,randn_c()*ones(OF));
channel9.replace_mid(k*OF,randn_c()*ones(OF));
channel10.replace_mid(k*OF,randn_c()*ones(OF));
channel11.replace_mid(k*OF,randn_c()*ones(OF));
channel12.replace_mid(k*OF,randn_c()*ones(OF));
channel13.replace_mid(k*OF,randn_c()*ones(OF));
channel14.replace_mid(k*OF,randn_c()*ones(OF));
channel15.replace_mid(k*OF,randn_c()*ones(OF));
channel16.replace_mid(k*OF,randn_c()*ones(OF));*/
}
norm_fading=1./sqrt(inv_dB(0)*norm(channel1)*norm(channel1)/sum_chips.length()/*+inv_dB(0)*norm(channel2)*norm(channel2)/sum_chips.length()+inv_dB(0)*norm(channel3)*norm(channel3)/sum_chips.length()+inv_dB(0)*norm(channel4)*norm(channel4)/sum_chips.length()+inv_dB(0)*norm(channel5)*norm(channel5)/sum_chips.length()+inv_dB(0)*norm(channel6)*norm(channel6)/sum_chips.length()+inv_dB(0)*norm(channel7)*norm(channel7)/sum_chips.length()+inv_dB(0)*norm(channel8)*norm(channel8)/sum_chips.length()+inv_dB(0)*norm(channel9)*norm(channel9)/sum_chips.length()+inv_dB(0)*norm(channel10)*norm(channel10)/sum_chips.length()+inv_dB(0)*norm(channel11)*norm(channel11)/sum_chips.length()+inv_dB(0)*norm(channel12)*norm(channel12)/sum_chips.length()+inv_dB(0)*norm(channel13)*norm(channel13)/sum_chips.length()+inv_dB(0)*norm(channel14)*norm(channel14)/sum_chips.length()+inv_dB(0)*norm(channel15)*norm(channel15)/sum_chips.length()+inv_dB(0)*norm(channel16)*norm(channel16)/sum_chips.length()*/);
fading.set_row(0,norm_fading*channel1);
/* fading.set_row(1,norm_fading*channel2);
fading.set_row(2,norm_fading*channel3);
fading.set_row(3,norm_fading*channel4);
fading.set_row(4,norm_fading*channel5);
fading.set_row(5,norm_fading*channel6);
fading.set_row(6,norm_fading*channel7);
fading.set_row(7,norm_fading*channel8);
fading.set_row(8,norm_fading*channel9);
fading.set_row(9,norm_fading*channel10);
fading.set_row(10,norm_fading*channel11);
fading.set_row(11,norm_fading*channel12);
fading.set_row(12,norm_fading*channel13);
fading.set_row(13,norm_fading*channel14);
fading.set_row(14,norm_fading*channel15);
fading.set_row(15,norm_fading*channel16);*/
for (int k=0;k<L;k++){
transmitted_symbols+=concat(zeros_c(k),elem_mult(to_cvec(sum_chips),fading.get_row(k)),zeros_c(L+1-k));
}
received_chips = channel(/*transmitted_symbols*/sum_chips);
cvec constellation;
int time_offset_estimate;
received_bits=modem->demodulate(received_chips,constellation,time_offset_estimate);
bvec received_bits_inverted=received_bits+bin(1);
//Generic Transmitter + First Receiver M&M + Costas
berc1.count(transmitted_bits, received_bits);
ber(i) = berc1.get_errorrate();
berc=berc1;
berc2.count(transmitted_bits, received_bits_inverted);
if(berc2.get_errorrate()<ber(i)){
ber(i) = berc2.get_errorrate();
berc=berc2;
}
cout << " Iteration " << j + 1 << ": ber = " << berc.get_errorrate() << endl;
if (berc.get_errors() > MaxNrOfErrors) {
cout << "Breaking on point " << i + 1 << " with " << berc.get_errors() << " errors." << endl;
break;
}
}
if (berc.get_errors() < MinNrOfErrors) {
cout << "Exiting Simulation on point " << i + 1 << endl;
break;
}
}
//Print results:
cout << endl;
cout << "EbN0dB = " << EbN0dB << endl;
cout << "ber = " << ber << endl;
}
MCDAAOFDM_BER_Test::MCDAAOFDM_BER_Test()
{
modem=new Modem_MCDAAOFDM();
int L=1;
int quasi_static=modem->Nfft+modem->Ncp;
cmat fading;
cvec channel1,channel2,channel3,channel4,channel5,channel6,channel7,channel8,channel9,channel10,channel11,channel12,channel13,channel14,channel15,channel16;
bvec transmitted_bits;
bvec received_bits;
cvec modulated_ofdm;
cvec transmitted_symbols;
cvec received_ofdm;
double norm_fading;
BERC berc;
AWGN_Channel channel;
vec EbN0dB = linspace(0, 40, 41);
vec EbN0 = pow(10, EbN0dB / 10);
double Eb = 1.0;
vec N0 = Eb * pow(EbN0, -1.0);
int NumOfBits = 1000000;
int MaxIterations = 10;
int MaxNrOfErrors = 200;
int MinNrOfErrors = 5;
vec ber;
ber.set_size(EbN0dB.size(), false);
ber.clear();
RNG_randomize();
for (int i=0;i<EbN0dB.length();i++){
cout << endl << "Simulating point nr " << i + 1 << endl;
berc.clear();
channel.set_noise(N0(i));
for (int j=0;j<MaxIterations;j++) {
transmitted_bits = randb(NumOfBits);
modulated_ofdm=sqrt(modem->Nfft+modem->Ncp)/sqrt(modem->Nfft)*modem->modulate_mask_qpsk(transmitted_bits,0);
transmitted_symbols.set_length(modulated_ofdm.length()+L+1);
transmitted_symbols.zeros();
fading.set_size(L,modulated_ofdm.length());
fading.zeros();
channel1.set_length(modulated_ofdm.length());
/* channel2.set_length(modulated_ofdm.length());
channel3.set_length(modulated_ofdm.length());
channel4.set_length(modulated_ofdm.length());
channel5.set_length(modulated_ofdm.length());
channel6.set_length(modulated_ofdm.length());
channel7.set_length(modulated_ofdm.length());
channel8.set_length(modulated_ofdm.length());
channel9.set_length(modulated_ofdm.length());
channel10.set_length(modulated_ofdm.length());
channel11.set_length(modulated_ofdm.length());
channel12.set_length(modulated_ofdm.length());
channel13.set_length(modulated_ofdm.length());
channel14.set_length(modulated_ofdm.length());
channel15.set_length(modulated_ofdm.length());
channel16.set_length(modulated_ofdm.length());*/
for(int k=0;k<modulated_ofdm.length()/quasi_static;k++){
channel1.replace_mid(k*quasi_static,ones_c(quasi_static));
//complex<double> random_complex= randn_c();
//double canal=sqrt(real(random_complex*conj(random_complex)));
//channel1.replace_mid(k*quasi_static,canal*ones_c(quasi_static));
//channel1.replace_mid(k*quasi_static,randn_c()*ones(quasi_static));
/* channel2.replace_mid(k*quasi_static,randn_c()*ones(quasi_static));
channel3.replace_mid(k*quasi_static,randn_c()*ones(quasi_static));
channel4.replace_mid(k*quasi_static,randn_c()*ones(quasi_static));
channel5.replace_mid(k*quasi_static,randn_c()*ones(quasi_static));
channel6.replace_mid(k*quasi_static,randn_c()*ones(quasi_static));
channel7.replace_mid(k*quasi_static,randn_c()*ones(quasi_static));
channel8.replace_mid(k*quasi_static,randn_c()*ones(quasi_static));
channel9.replace_mid(k*quasi_static,randn_c()*ones(quasi_static));
channel10.replace_mid(k*quasi_static,randn_c()*ones(quasi_static));
channel11.replace_mid(k*quasi_static,randn_c()*ones(quasi_static));
channel12.replace_mid(k*quasi_static,randn_c()*ones(quasi_static));
channel13.replace_mid(k*quasi_static,randn_c()*ones(quasi_static));
channel14.replace_mid(k*quasi_static,randn_c()*ones(quasi_static));
channel15.replace_mid(k*quasi_static,randn_c()*ones(quasi_static));
channel16.replace_mid(k*quasi_static,randn_c()*ones(quasi_static));*/
}
norm_fading=1./sqrt(inv_dB(0)*norm(channel1)*norm(channel1)/modulated_ofdm.length()/*+inv_dB(0)*norm(channel2)*norm(channel2)/modulated_ofdm.length()+inv_dB(0)*norm(channel3)*norm(channel3)/modulated_ofdm.length()+inv_dB(0)*norm(channel4)*norm(channel4)/modulated_ofdm.length()+inv_dB(0)*norm(channel5)*norm(channel5)/modulated_ofdm.length()+inv_dB(0)*norm(channel6)*norm(channel6)/modulated_ofdm.length()+inv_dB(0)*norm(channel7)*norm(channel7)/modulated_ofdm.length()+inv_dB(0)*norm(channel8)*norm(channel8)/modulated_ofdm.length()+inv_dB(0)*norm(channel9)*norm(channel9)/modulated_ofdm.length()+inv_dB(0)*norm(channel10)*norm(channel10)/modulated_ofdm.length()+inv_dB(0)*norm(channel11)*norm(channel11)/modulated_ofdm.length()+inv_dB(0)*norm(channel12)*norm(channel12)/modulated_ofdm.length()+inv_dB(0)*norm(channel13)*norm(channel13)/modulated_ofdm.length()+inv_dB(0)*norm(channel14)*norm(channel14)/modulated_ofdm.length()+inv_dB(0)*norm(channel15)*norm(channel15)/modulated_ofdm.length()+inv_dB(0)*norm(channel16)*norm(channel16)/modulated_ofdm.length()*/);
fading.set_row(0,norm_fading*channel1);
/* fading.set_row(1,norm_fading*channel2);
fading.set_row(2,norm_fading*channel3);
fading.set_row(3,norm_fading*channel4);
fading.set_row(4,norm_fading*channel5);
fading.set_row(5,norm_fading*channel6);
fading.set_row(6,norm_fading*channel7);
fading.set_row(7,norm_fading*channel8);
fading.set_row(8,norm_fading*channel9);
fading.set_row(9,norm_fading*channel10);
fading.set_row(10,norm_fading*channel11);
fading.set_row(11,norm_fading*channel12);
fading.set_row(12,norm_fading*channel13);
fading.set_row(13,norm_fading*channel14);
fading.set_row(14,norm_fading*channel15);
fading.set_row(15,norm_fading*channel16);*/
for (int k=0;k<L;k++){
transmitted_symbols+=concat(zeros_c(k),elem_mult(to_cvec(modulated_ofdm),fading.get_row(k)),zeros_c(L+1-k));
}
received_ofdm = channel(transmitted_symbols);
//received_chips = sum_chips;
cvec constellation;
vec estimated_channel;
double metric;
//bool is_ofdm=modem->detection(received_ofdm,metric);
modem->time_offset_estimate=0;
modem->frequency_offset_estimate=0;
cvec demodulated_ofdm_symbols=modem->equalizer_fourth_power(received_ofdm,0,estimated_channel);
received_bits=modem->demodulate_mask_gray_qpsk(demodulated_ofdm_symbols,0,constellation);
berc.count(transmitted_bits, received_bits);
ber(i) = berc.get_errorrate();
cout << " Iteration " << j + 1 << ": ber = " << berc.get_errorrate() << endl;
if (berc.get_errors() > MaxNrOfErrors) {
cout << "Breaking on point " << i + 1 << " with " << berc.get_errors() << " errors." << endl;
break;
}
}
if (berc.get_errors() < MinNrOfErrors) {
cout << "Exiting Simulation on point " << i + 1 << endl;
break;
}
}
//Print results:
cout << endl;
cout << "EbN0dB = " << EbN0dB << endl;
cout << "ber = " << ber << endl;
}
vec filter_spectrum(const vec &a, const vec &b, int nfft)
{
vec s = sqr(abs(elem_div(fft(to_cvec(a), nfft), fft(to_cvec(b), nfft))));
s.set_size(nfft / 2 + 1, true);
return s;
}
//Correlation
void xcorr(const cvec &x, const cvec &y, cvec &out, const int max_lag, const std::string scaleopt, bool autoflag)
{
int N = std::max(x.length(), y.length());
//Compute the FFT size as the "next power of 2" of the input vector's length (max)
int b = ceil_i(::log2(2.0 * N - 1));
int fftsize = pow2i(b);
int end = fftsize - 1;
cvec temp2;
if (autoflag == true) {
//Take FFT of input vector
cvec X = fft(zero_pad(x, fftsize));
//Compute the abs(X).^2 and take the inverse FFT.
temp2 = ifft(elem_mult(X, conj(X)));
}
else {
//Take FFT of input vectors
cvec X = fft(zero_pad(x, fftsize));
cvec Y = fft(zero_pad(y, fftsize));
//Compute the crosscorrelation
temp2 = ifft(elem_mult(X, conj(Y)));
}
// Compute the total number of lags to keep. We truncate the maximum number of lags to N-1.
int maxlag;
if ((max_lag == -1) || (max_lag >= N))
maxlag = N - 1;
else
maxlag = max_lag;
//Move negative lags to the beginning of the vector. Drop extra values from the FFT/IFFt
if (maxlag == 0) {
out.set_size(1, false);
out = temp2(0);
}
else
out = concat(temp2(end - maxlag + 1, end), temp2(0, maxlag));
//Scale data
if (scaleopt == "biased")
//out = out / static_cast<double_complex>(N);
out = out / static_cast<std::complex<double> >(N);
else if (scaleopt == "unbiased") {
//Total lag vector
vec lags = linspace(-maxlag, maxlag, 2 * maxlag + 1);
cvec scale = to_cvec(static_cast<double>(N) - abs(lags));
out /= scale;
}
else if (scaleopt == "coeff") {
if (autoflag == true) // Normalize by Rxx(0)
out /= out(maxlag);
else { //Normalize by sqrt(Rxx(0)*Ryy(0))
double rxx0 = sum(abs(elem_mult(x, x)));
double ryy0 = sum(abs(elem_mult(y, y)));
out /= std::sqrt(rxx0 * ryy0);
}
}
else if (scaleopt == "none") {}
else
it_warning("Unknow scaling option in XCORR, defaulting to <none> ");
}
int tf_csim_casdec_x()
{
CSIM::fir_x fir_x1, fir_x2, fir_x3;
CSIM::counter cnt1, cnt2, cnt3;
CSIM::wgn_x wgn_x1;
CSIM::casdec_x casdec_x1;
int N;
cvec c0;
cvec x_x;
bvec ce, ce1, ce2, ce3;
cvec ya_x1, ya_x2, ya_x3;
cmat ya, yb, yc;
//----------------------------------------
// test of csim
//----------------------------------------
cout << "CSIM::casdec_x Test" << endl;
try {
// mav<4>
c0="(0.25,0.0) (0.25,0.0) (0.25, 0.0) (0.25,0.0)";
cout << "c0=" << c0 << endl;
// discrete cascade settings
fir_x1.set_taps(c0); fir_x1.reset();
fir_x2.set_taps(c0); fir_x2.reset();
fir_x3.set_taps(c0); fir_x3.reset();
cnt1.set_N(2); cnt1.reset();
cnt2.set_N(2); cnt2.reset();
cnt3.set_N(2); cnt3.reset();
cout << "discrete cascade settings " << endl;
// device cascade settings
casdec_x1.set_size(3);
casdec_x1.set_taps(c0);
casdec_x1.reset();
cout << "device cascade settings " << endl;
N=256;
// clock and signal
ce.set_length(N); ce.ones(); // clock
cout << "ce=" << ce << endl;
// discrete cascade proc
while (1) {
x_x = wgn_x1.generate(ce); // source - random mean = (0.0+j0.0) sigma =1.0
cout << "x_x=" << x_x << endl;
ya_x1 = fir_x1.process(ce,x_x); ce1 = cnt1.generate(ce);
ya_x2 = fir_x2.process(ce1,ya_x1); ce2 = cnt2.generate(ce1);
ya_x3 = fir_x3.process(ce2,ya_x2); ce3 = cnt3.generate(ce2);
ya.set_size(N,2);
ya.set_col(0,ya_x3);
ya.set_col(1,to_cvec(to_vec(ce3), zeros(ce3.length())));
// cout << "discrete cascade proc " << endl;
// device cascade proc
yb = casdec_x1.process(ce, x_x);
// cout << "device cascade proc " << endl;
yc.set_size(N,4);
yc.set_col(0, ya.get_col(0));
yc.set_col(1, yb.get_col(0));
yc.set_col(2, ya.get_col(1));
yc.set_col(3, yb.get_col(1));
cout << "yc=" << endl << yc << endl;
}
}
catch (sci_exception except) {
cout<< "\n sci exception:" << endl <<except.get_msg() <<":" << except.get_info() << endl;
}
return 0;
}
