%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Creative Commons % Attribution-Noncommercial 2.5 India % You are free: % to Share — to copy, distribute and transmit the work % to Remix — to adapt the work % Under the following conditions: % Attribution. You must attribute the work in the manner % specified by the author or licensor (but not in any way % that suggests that they endorse you or your use of the work). % Noncommercial. You may not use this work for commercial purposes. % For any reuse or distribution, you must make clear to others the % license terms of this work. The best way to do this is with a % link to this web page. % Any of the above conditions can be waived if you get permission % from the copyright holder. % Nothing in this license impairs or restricts the author's moral rights. % http://creativecommons.org/licenses/by-nc/2.5/in/ % Script for simulating 16-QAM transmission and reception and compare the % simulated and theoretical symbol error probability % Checked for proper operation with Octave Version 3.0.0 % Author : Krishna % Email : krishna@dsplog.com % Version : 1.0 % Date : 9 December 2007 % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % symbol error rate for 16-QAM modulation % symbol error rate for 16-QAM modulation clear N = 2*10^5; % number of symbols alpha16qam = [-3 -1 1 3]; % 16-QAM alphabets Es_N0_dB = [0:20]; % multiple Es/N0 values ipHat = zeros(1,N); for ii = 1:length(Es_N0_dB) ip = randsrc(1,N,alpha16qam) + j*randsrc(1,N,alpha16qam); s = (1/sqrt(10))*ip; % normalization of energy to 1 n = 1/sqrt(2)*[randn(1,N) + j*randn(1,N)]; % white guassian noise, 0dB variance y = s + 10^(-Es_N0_dB(ii)/20)*n; % additive white gaussian noise % demodulation y_re = real(y); % real part y_im = imag(y); % imaginary part ipHat_re(find(y_re< -2/sqrt(10))) = -3; ipHat_re(find(y_re > 2/sqrt(10))) = 3; ipHat_re(find(y_re>-2/sqrt(10) & y_re<=0)) = -1; ipHat_re(find(y_re>0 & y_re<=2/sqrt(10))) = 1; ipHat_im(find(y_im< -2/sqrt(10))) = -3; ipHat_im(find(y_im > 2/sqrt(10))) = 3; ipHat_im(find(y_im>-2/sqrt(10) & y_im<=0)) = -1; ipHat_im(find(y_im>0 & y_im<=2/sqrt(10))) = 1; ipHat = ipHat_re + j*ipHat_im; nErr(ii) = size(find([ip- ipHat]),2); % couting the number of errors end simBer = nErr/N; theoryBer = 3/2*erfc(sqrt(0.1*(10.^(Es_N0_dB/10)))); close all figure semilogy(Es_N0_dB,theoryBer,'b.-','LineWidth',2); hold on semilogy(Es_N0_dB,simBer,'mx-','Linewidth',2); axis([0 20 10^-5 1]) grid on legend('theory', 'simulation'); xlabel('Es/No, dB') ylabel('Symbol Error Rate') title('Symbol error probability curve for 16-QAM modulation')