bfsk.zip_All Clear_SNRdB_bfsk snr matlab_waitbar

clear all snrdB_min = 0; snrdB_max = 10; % SNR (in dB)limits snrdB = snrdB_min:1:snrdB_max; Nsymbols = input('Enter number of symbols > '); snr = 10.^(snrdB/10); % convert from dB h = waitbar(0,'SNR Iteration'); len_snr = length(snrdB); for j=1:len_snr % increment SNR waitbar(j/len_snr) sigma = sqrt(1/(2*snr(j))); % noise standard deviation error_count = 0; for k=1:Nsymbols % simulation loop begins d = round(rand(1)); % data if d ==0 x_d = 1; % direct transmitter output x_q = 0; % quadrature transmitter output else x_d = 0; % direct transmitter output x_q = 1; % quadrature transmitter output end n_d = sigma*randn(1); % direct noise component n_q = sigma*randn(1); % quadrature noise component y_d = x_d + n_d; % direct receiver input y_q = x_q + n_q; % quadrature receiver input if y_d > y_q % test condition d_est = 0; % conditional data estimate else d_est = 1; % conditional data estimate end if (d_est ~= d) error_count = error_count + 1; % error counter end end % simulation loop ends errors(j) = error_count; % store error count for plot end close(h) ber_sim = errors/Nsymbols; % BER estimate % theoretical BER semilogy(snrdB,ber_sim,'o') axis([snrdB_min snrdB_max 0.0001 1]) xlabel('SNR in dB') ylabel('BER') legend('Simulation') % End of script file.