1. Get the code method (with the instructions of the experimental topic)

Obtain code method 1:
The full code has uploaded my resources:[Digital signal modulation] Based on the Matlab QAM signal generation and demodulation [Matlab source code 1684]

Obtain code method 2:
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2. Partial source code

clc;close all
nsymbol= 100000;                                              %Random signal length
M=16;
SNR=1:15;                                                     %Signal to noise ratio, unit DB
snr1=10.^(SNR/10);                                            %Turn DB to a non -linear way
graycode=[0 1 3 2 4 5 7 6 12 13 15 14 8 9 11 10];             %Gray mapping
data=randi([0,15],1,nsymbol);                                 %Generate random signals
data1=graycode(data+1);                                       %Gray mapping
tx=qammod(data1,M);                                           %16QAM modulation
spow=norm(tx).^2/nsymbol;                                     %a+The square of BJ's mold, that is, power; the average power except the entire symbol is except the entire symbol
for i= 1:length(SNR) 
    rx=awgn(tx,SNR(i),spow);                                  %Kagosa white noise
    yout=qamdemod(rx,M);                                      %16QAM demodulation
    data_out=graycode(yout+1);                                %Gray
    [err1,errb(i)]=biterr(data,data_out,log2(M));             %Experimental error bid rate
    [err2,errs(i)]=symerr(data,data_out);                     %Experimental error rate
end
%%  Calculate theoretical value and compare the experimental value
p4=2*(1-1/sqrt(M))*qfunc(sqrt(3*snr1/(M-1)));                 %Theoretical error rate
terrs=1-(1-p4).^2;
terrb=1/log2(M)*terrs;                                        %Theoretical error bitting rate

Third, run results

Fourth, Matlab version and reference literature

1 Matlab version
2014a

2 References
[1] Shen Ziyang. Professional Matlab signal processing [M]. Tsinghua University Press, 2015.
[2] Gao Baojian, Peng Jinye, Wang Lin, Pan Jianshou. Signal and system -use matlab analysis and implementation [m]. Tsinghua University Press, 2020.
[3] MATLAB implementation [m]. Electronic Industry Press, 2018. Electronic Industry Press, 2018.