NOMA

782161565

NOMA下行两用户的误码率matlab基础仿真代码：

1. clc; clear variables; close all;
   
2. 
   
3. N = 10^5;               %Number of monte carlo simulations
   
4. SNR = 0:30;             %SNR range in dB
   
5. snr = db2pow(SNR);      %SNR range in linear scale
   
6. 
   
7. %Generate random data bits for transmission
   
8. x1 = randi([0 1],1,N);  %Data bits of user 1
   
9. x2 = randi([0 1],1,N);  %Data bits of user 2
   
10. 
    
11. %Do BPSK modulation of data
    
12. xmod1 = 2*x1 - 1;
    
13. xmod2 = 2*x2 - 1;
    
14. 
    
15. %Set power weights for users
    
16. a1 = 0.75; a2 = 0.25;
    
17. 
    
18. %Do superposition coding
    
19. x = sqrt(a1)*xmod1 + sqrt(a2)*xmod2;
    
20. 
    
21. %Add AWGN to x (Transmit x through an AWGN channel)
    
22. for u = 1:length(snr)
    
23.     y1 = awgn(x,SNR(u),'measured');  %Received signal at user 1 corrupted by AWGN
    
24.     y2 = awgn(x,SNR(u),'measured'); %Received signal at user 2 corrupted by AWGN
    
25.    
    
26.     %AT USER 1
    
27.     %Direct decoding of x from y1
    
28.     x1_hat = ones(1,N); %just a buffer
    
29.     x1_hat(y1 < 0) = 0;
    
30.    
    
31.     %AT USER 2
    
32.     %Direct decoding of x from y2
    
33.     x11_est = ones(1,N); %just a buffer
    
34.     x11_est(y2 < 0) = 0; %Estimate user 1's signal first
    
35.     x11_est(x11_est == 0) = -1; %Remodulate user 1's signal
    
36.     %Subtract remodulated x11_est component from y2
    
37.     rem = y2 - sqrt(a1)*x11_est;
    
38.    
    
39.     %Decode x2 from rem
    
40.     x2_hat = zeros(1,N);
    
41.     x2_hat(rem>0) = 1;
    
42.    
    
43.     %Estimate BER
    
44.     ber1(u) = biterr(x1,x1_hat)/N;
    
45.     ber2(u) = biterr(x2,x2_hat)/N;
    
46. end
    
47. 
    
48. %plot BER curves
    
49. semilogy(SNR, ber1, 'linewidth', 1.5); hold on;
    
50. semilogy(SNR, ber2, 'linewidth', 1.5); grid on;
    
51. legend('User 1 \alpha_1 = 0.75','User 2 \alpha_2 = 0.25');
    
52. xlabel('SNR (dB)');
    
53. ylabel('BER');
    
54. title('BER graph for NOMA in AWGN channel');

复制代码