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1661294de53675cc11305a15fbbd5f453750222c
openairinterface5g/openair1/SIMULATION/LTE_PHY/Abstraction/Training/training_abstraction.m
T
Cedric Roux 56c66c09aa - Fix: avoid infinite loop on mulitcast read thread if no data to read 
Pre-ci test passed

git-svn-id: http://svn.eurecom.fr/openair4G/trunk@4000 818b1a75-f10b-46b9-bf7c-635c3b92a50f
2013-06-25 09:05:02 +00:00

318 lines
12 KiB
Matlab
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%***************************************************************************************
% Some basic initializations
%***************************************************************************************
global SINR_p BLER_meas snr bler SINR_awgn abs_mode modu Pm tx_mode alpha seta mi_file mi_2_file p
set(0, 'DefaultLineMarkerSize', 10);
set(0, 'Defaultaxesfontsize', 10);
set(0, 'DefaultLineLineWidth', 2);
set(0, 'DefaultAxesFontName', 'Helvetica');
set(0, 'DefaultTextFontName', 'Helvetica');
plot_style = {'b*';'r*';'g*';'y*';'k*';...
'bo';'ro';'go';'yo';'ko';...
'bs';'rs';'gs';'ys';'ks';...
'bd';'rd';'gd';'yd';'kd';...
'bx';'rx';'gx';'yx';'kx';...
'b+';'r+';'g+';'y+';'k+'};
echo off;
%***************************************************************************************
% Input Parameters used for the training of adjustment Factors (betas)
%***************************************************************************************
s2=[]; s3=[]; ss=[];
tx_mode=transmission_mode;
%1--> SISO, 2 --> Alamouti, 5 --> MU-MIMO ,6 --> TX Beamforming
% tells which transmission mode is to be abstracted.
abs_mode=abstraction_mode;
% 0:MIESM (M2-MIESM), 1:EESM, 2:IA-MIESM (M1-MIESM)
%tells which abstraction methodology is to be used.
Pm=100;
%2*50 QPSK
% Used for calculating RBIR
modu=4;
mi_file = strcat(userdir,'/SIMULATION/LTE_PHY/Abstraction/matFiles/siso_MI_abs_4Qam.mat');
mi_2_file = strcat(userdir,'/SIMULATION/LTE_PHY/Abstraction/matFiles/data_mode5_4_4_morerealizations.mat');
% Modulation used.
p=50;
save_out=save_output;
out_s1 = strcat(' Training for Transmission Mode = ', num2str(tx_mode));
out_s2 = strcat(' Training for Abstraction Mode = ', num2str(abs_mode));
out_s3 = strcat(' Saving Results = ', num2str(save_out));
disp('*******************************************************************');
disp(out_s1);
disp(out_s2);
disp(out_s3);
disp('*******************************************************************');
if (save_out)
if(tx_mode==5)
if(abs_mode==0)
out_fname= fullfile(M2_path, strcat('tx_', num2str(tx_mode), '_abs_M2_MIESM'));
out_s = 'M2 MIESM';
else
if (abs_mode==2)
out_fname= fullfile(M1_path, strcat('tx_', num2str(tx_mode), '_abs_M1_MIESM'));
out_s = 'M1 MIESM';
else
out_fname= fullfile(EESM_path, strcat('tx_', num2str(tx_mode), '_abs_EESM'));
out_s = 'EESM';
end
end
else
if(abs_mode == 1)
out_fname= fullfile(EESM_path, strcat('tx_', num2str(tx_mode), '_abs_EESM'));
out_s = 'EESM';
else
out_fname= fullfile(MIESM_path, strcat('tx_', num2str(tx_mode), '_abs_MIESM'));
out_s = 'MIESM';
end
end
fid = fopen(strcat(out_fname, '.tex'),'w');
fprintf(fid,'\\documentclass[a4paper,conference]{IEEEtran}\n');
fprintf(fid,'\\usepackage{epsfig}\n');
fprintf(fid,'\\usepackage{rotating}\n');
fprintf(fid,'\\usepackage{amsmath}\n');
fprintf(fid,'\\usepackage{amsfonts}\n');
fprintf(fid,'\\usepackage{amssymb}\n');
fprintf(fid,'\\usepackage{graphics}\n');
fprintf(fid,'\\usepackage{mathtools}\n');
fprintf(fid,'\\IEEEoverridecommandlockouts\n');
fprintf(fid,'\\title{%s}\n',sprintf('Results of %s for LTE Transmission Mode %d',out_s, tx_mode));
fprintf(fid,'\\author{\\IEEEauthorblockN{Imran Latif}\n');
fprintf(fid,'\\IEEEauthorblockA{Eurecom\\\\\n');
fprintf(fid,'2229, Route des Cretes, B.P. 193\\\\\n');
fprintf(fid,'06904 Sophia Antipolis, France\\\\\n');
fprintf(fid,'Email: (first name.last name)@eurecom.fr}\n');
fprintf(fid,'}\n');
fprintf(fid,'\\begin{document}\n');
fprintf(fid,'\\maketitle\n');
fprintf(fid,'\\begin{abstract}\n');
fprintf(fid,'\\end{abstract}\n');
fprintf(fid,'\\section{Results}\n');
end
%***************************************************************************************
% Main Execution Loop starts from here:
%***************************************************************************************
for m=1:1:length(mcs)
if(mcs(m) >9 && mcs(m) < 17)
modu=16;
Pm=200; %4*50 16QAM
mi_file = strcat(userdir,'/SIMULATION/LTE_PHY/Abstraction/siso_MI_abs_16Qam.mat');
mi_2_file = strcat(userdir,'/SIMULATION/LTE_PHY/Abstraction/matFiles/data_mode5_16_16.mat');
else if(mcs(m) > 16 && mcs(m) < 28)
modu = 64;
Pm=300; %6 *50 64QAM
mi_file = strcat(userdir,'/SIMULATION/LTE_PHY/Abstraction/siso_MI_abs_64Qam.mat');
end
end
%***************************************************************************************
%Reference AWGN Curves
%***************************************************************************************
data = dlmread(fullfile(awgn_path, strcat('awgn_bler_tx1_mcs', num2str(mcs(m)), '.csv')),';',1,0);
A = data(:,1);
B = data(:,5)./data(:,6); % round 1
[bler I J] = unique(B);
bler = sort(bler,1,'descend');
I = sort(I,1,'ascend');
snr = A(I);
%***************************************************************************************
% Data Extraction on Sub carrier basis data file saved using dlsim and reference
% SINR Calculation based on Reference AWGN Curve
%***************************************************************************************
eval(['data_all = data_all' num2str(mcs(m)) ';']);
data_all = data_all(data_all(:,end)<bler(1),:);
data_all = data_all(data_all(:,end)>=bler(end),:);
BLER_meas = data_all(:,end);
SINR_awgn = interp1(bler, snr, BLER_meas,'linear','extrap');
SINR_awgn = SINR_awgn';
%***************************************************************************************
% Calculation of SINR per subcarrier
%***************************************************************************************
%for SISO
switch(tx_mode)
case 1
ch_tmp = data_all(:,2:51);
abs_channel = (abs(ch_tmp).^2);
input_snr = 10.^(data_all(:,1)/10);
input_snr = repmat(input_snr,1,50);
SINR_p = 10*log10(input_snr.*abs_channel);
case 2
ch1_tmp = data_all(:,2:2:100);
ch2_tmp = data_all(:,3:2:101);
abs_channel1 = (abs(ch1_tmp).^2)/2;
abs_channel2 = (abs(ch2_tmp).^2)/2;
input_snr = 10.^(data_all(:,1)/10);
input_snr = repmat(input_snr,1,50);
SINR_p = 10*log10(input_snr.*abs_channel1 + input_snr.*abs_channel2);%- 10*log10(2);
case 5
prec1_tmp = data_all(:,203:end-1);
prec2_tmp = arrayfun(@opposite_q,prec1_tmp);
q1 = arrayfun(@demap_q,prec1_tmp);
q2 = arrayfun(@demap_q,prec2_tmp);
ch1_tmp = data_all(:,2:2:100);
ch2_tmp = data_all(:,3:2:101);
snr_tmp = 10.^(data_all(:,1)/10);
snr_tmp = repmat(snr_tmp,1,50);
% h1 = [ch1_tmp ch2_tmp];
% p1 = [1; q1];
% p2 = [1; q2];
alpha =(1/2)*abs(ch1_tmp + q1.*ch2_tmp);
%seta = abs(((conj(h1*p1))*(h1*p2))/(abs(h1*p1)));
%seta = (1/2)*abs(((conj(ch1_tmp + q1.*ch2_tmp)).*(ch1_tmp + q2.*ch2_tmp))./(abs(ch1_tmp + q1.*ch2_tmp)));
%alpha =sqrt(1/2)*abs(ch1_tmp + q1.*ch2_tmp);
seta = (1/2)*((abs(ch1_tmp + q2.*ch2_tmp)));
% alpha =abs(ch1_tmp + q1.*ch2_tmp);
if (abs_mode==2 )
SINR_p = 10*log10(snr_tmp.*(alpha.^2));%-10*log10(2);
else
SINR_p = 10*log10((snr_tmp.*(alpha.^2)) ./ ((snr_tmp.*(seta.^2)) + 1));
end
case 6
prec_tmp = data_all(:,203:end-1);
q = arrayfun(@demap_q,prec_tmp);
ch1_tmp = data_all(:,2:2:100);
ch2_tmp = data_all(:,3:2:101);
snr_tmp = 10.^(data_all(:,1)/10);
snr_tmp = repmat(snr_tmp,1,50);
ch_composite = (abs(ch1_tmp + q.*ch2_tmp))/sqrt(2);
SINR_p = 10*log10((snr_tmp.*((ch_composite).^2)));
end
%***************************************************************************************
% for coarse beta calculation:
%***************************************************************************************
% beta_vec = 1:0.1:30;
% delta = zeros(size(beta_vec));
% for beta=1:length(beta_vec)
% delta(beta)=delta_BLER_1((beta_vec(beta)));
% end
% [val ind] = min(delta);
% opt_beta_new(mcs(m)) = beta_vec(ind);
%***************************************************************************************
% for optmimized betas calculation using fminsearch
%***************************************************************************************
opt_beta=0;
beta_out=ones(1,2);
[opt_beta, MSE1] = fminsearch(@delta_BLER_1,1);
[beta_out, MSE2] = fminsearch(@delta_BLER_1,[1 1]);
%***************************************************************************************
% Calculation of Effective SINR based on optimized beta values
%***************************************************************************************
SINR_eff_single_beta = sinr_Eff_Calc(opt_beta);
SINR_eff_dual_beta = sinr_Eff_Calc(beta_out);
%***************************************************************************************
%MSE Calculation
%***************************************************************************************
MSE_final_single_beta(m) = mean((SINR_awgn - SINR_eff_single_beta).^2);
MSE_final_dual_beta(m) = mean((SINR_awgn - SINR_eff_dual_beta).^2);
single_Optimum_Beta(m) = opt_beta;
dual_Optimum_Beta1(m) = beta_out(1);
dual_Optimum_Beta2(m) = beta_out(2);
%***************************************************************************************
% BLER Plot w.r.t Mean Effective SINR
%***************************************************************************************
% figure;
% avg_SINR_p = mean(SINR_p');
% hist(avg_SINR_p)
% s = strcat('Average_SINR_p, MCS = ',num2str(mcs(m)));
% title(2)
% figure;
% grid on
% semilogy(avg_SINR_p,BLER_meas,plot_style{m+1})
% xlim([-8 15])
% ylim([1e-3 1])
% s = strcat('LTE TM1 Avergae Abstraction MCS ', num2str(mcs(m)));
% title(s);
% ylabel 'BLER'
% xlabel 'SINR_{average}'
% s2 = strcat('BLER_{meas} MCS ', num2str(mcs(m)));
% legend(s2, 'Location', 'Best');
%***************************************************************************************
% BLER Plot w.r.t Effective SINR
%***************************************************************************************
% figure;
% hist(SINR_eff)
% s = strcat('SINR_eff, MCS = ',num2str(mcs(m)));
% title(s)
create_plots;
end
disp(' MCS dual_Beta1 dual_Beta2 MSE beta2=beta1 MSE');
disp([mcs' dual_Optimum_Beta1' dual_Optimum_Beta2' MSE_final_dual_beta' single_Optimum_Beta' MSE_final_single_beta'])
%***************************************************************************************
%For saving the files
%***************************************************************************************
if(save_out)
fprintf(fid,'\\begin{table}[t]\n');
fprintf(fid,'\\centering\n');
fprintf(fid,'\\caption{beta1, beta2 and Mean Squared Error (MSE) Values for abstraction}\n');
fprintf(fid,'\\begin{tabular}{ | c | c | c | c | c | c |}\n');
fprintf(fid,'\\hline\n');
fprintf(fid,'\\textbf{MCS} & \\textbf{Beta1} & \\textbf{Beta2} & \\textbf{MSE} & \\textbf{Beta1=Beta2} & \\textbf{MSE} \\\\ \\hline');
for in=1:length(mcs)
fprintf(fid,'%d & %3.5f & %3.5f & %01.5f & %3.5f & %01.5f \\\\ \\hline\n',mcs(in), dual_Optimum_Beta1(in), dual_Optimum_Beta2(in), MSE_final_dual_beta(in), single_Optimum_Beta(in), MSE_final_single_beta(in));
end
fprintf(fid,'\\end{tabular}\n');
fprintf(fid,'\\end{table}\n');
dlmwrite(fullfile(pathname,strcat(ss, '_beta1.csv')), dual_Optimum_Beta1, 'delimiter', ';');
dlmwrite(fullfile(pathname,strcat(ss, '_beta2.csv')), dual_Optimum_Beta2, 'delimiter', ';');
dlmwrite(fullfile(pathname,strcat(ss, '.csv')), single_Optimum_Beta, 'delimiter', ';');
dlmwrite(fullfile(pathname,strcat(ss, '_mse.csv')), MSE_final_dual_beta, 'delimiter', ';');
dlmwrite(fullfile(pathname,strcat(ss, '_mse.csv')), MSE_final_single_beta, 'delimiter', ';');
fprintf(fid,'\\end{document}\n');
fclose(fid);
%system(sprintf('latex %s.tex', out_fname));
%system(sprintf('dvipdf %s.dvi', out_fname));
end
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