matlab-通过matlab对比2PSK,4PSK,8PSK,16PSK的误码率,无符号率以及星座图-源码

clc; clear; close all; warning off; addpath(genpath(pwd)); %**************************************************************************** %更多关于matlab和fpga的搜索“fpga和matlab”的CSDN博客: %matlab/FPGA项目开发合作 %https://blog.csdn.net/ccsss22?type=blog %**************************************************************************** it=250000; EbNo=0:16; sigma=1./sqrt(8*(10.^(EbNo./10))); error = zeros(1,length(sigma)); BER=zeros(1,length(sigma)); BER_analytical=zeros(1,length(sigma)); BER_theoretical=zeros(1,length(sigma)); const_x=zeros(1,it); const_y=zeros(1,it); for k = 1:length(sigma) for i=1:it x=rand(); %%%%%%%%% mapping of symbol %%%%%%%%%%% if x <= 0.0625 symbol=1; A=[1 0]; else if x <= 0.125 && x > 0.0625 symbol=2; A=[0.923 0.38]; else if x <= 0.1875 && x > 0.125 symbol = 3; A=[0.707 0.707]; else if x <= 0.25 && x > 0.1875 symbol = 4; A=[0.38 0.923]; else if x <= 0.3125 && x > 0.25 symbol = 5; A=[0 1]; else if x <= 0.375 && x > 0.3125 symbol = 6; A=[-0.38 0.923]; else if x <= 0.4375 && x > 0.375 symbol = 7; A=[-0.707 0.707]; else if x <= 0.5 && x > 0.4375 symbol=8; A=[-0.923 0.38]; else if x <= 0.5625 && x > 0.5 symbol=9; A=[-1 0]; else if x <= 0.625 && x > 0.5625 symbol=10; A=[-0.923 -0.38]; else if x <= 0.6875 && x > 0.625 symbol=11; A=[-0.707 -0.707]; else if x <= 0.75 && x > 0.6875 symbol=12; A=[-0.382 -0.923]; else if x <= 0.8125 && x > 0.75 symbol=13; A=[0 -1]; else if x <= 0.875 && x > 0.8125 symbol=14; A=[0.382 -0.923]; else if x <= 0.9375 && x > 0.875 symbol=15; A=[0.707 -0.707]; else symbol=16; A=[0.923 -0.38]; end end end end end end end end end end end end end end end %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%% addition of noise %%%%%%%%%%% Inoise = sigma(k) * randn; Qnoise = sigma(k) * randn; Ircv = A(1) + Inoise; Qrcv = A(2) + Qnoise; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% B=[Ircv Qrcv]; const_x(i)=B(1); const_y(i)=B(2); %%%%%%%% Symbol Detection %%%%%%%%%%%%% B_Mag=sqrt((Ircv*Ircv)+(Qrcv*Qrcv)); C=dot(A,B); C=C/B_Mag; theta=acosd(C); if theta < 11.25 error(k)=error(k); else error(k)=error(k)+1; end %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% end; %%%%%%%% BER and SER calculations %%%%% BER_analytical(k)=error(k)/(4*it); BER_theoretical(k)=.25*erfc(.137/(sigma(k))); SER_analytical(k)=error(k)/(it); SER_theoretical(k)=erfc(.137/(sigma(k))); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% end semilogy(EbNo,BER_analytical,'-red+','LineWidth',2); hold on; semilogy(EbNo,BER_theoretical,'-.blueo','LineWidth',2); xlabel('EbNo in dB'); ylabel('BER in log scale'); title('BER v/s EbNo for 16PSK'); legend('Simulation','Theoretical'); grid on; figure; semilogy(EbNo,SER_analytical,'-red+','LineWidth',2); hold on; semilogy(EbNo,SER_theoretical,'-.blueo','LineWidth',2); xlabel('EbNo in dB'); ylabel('SER in log scale'); title('SER v/s EbNo for 16-PSK'); legend('Simulation','Theoretical'); grid on; figure; scatter(const_x,const_y,'*'); title('Constellation for 16-PSK'); save R16.mat