Commit | Line | Data |
---|---|---|
f9a73e9e AIL |
1 | numSymbs = 5e4; |
2 | M = 4; | |
3 | ||
4 | Rsym = 2.5e10; % symbol rate (sym/sec) | |
5 | Tsym = 1 / Rsym; % symbol period (sec) | |
6 | ||
7 | rolloff = 0.25; | |
8 | span = 6; % filter span | |
9 | sps = 2; % samples per symbol | |
10 | ||
11 | fs = Rsym * sps; % sampling freq (Hz) | |
12 | Tsamp = 1 / fs; | |
13 | ||
14 | t = (0 : 1 / fs : numSymbs / Rsym + (1.5 * span * sps - 1) / fs).'; | |
15 | ||
16 | ||
17 | power_dBm = -3:0.25:4; | |
18 | power = 10 .^ (power_dBm / 10) * 1e-3; % watts | |
19 | ||
20 | Es = power * Tsym; % joules | |
21 | Eb = Es / log2(M); % joules | |
22 | ||
23 | N0ref_dB = 10; % Eb/N0 at power = 1mW | |
24 | %% Fix N0, such that Eb/N0 = N0ref_dB at power = 1mW | |
25 | N0 = 1e-3 * Tsym / (log2(M) * 10 ^ (N0ref_dB / 10)); % joules | |
26 | ||
27 | ||
28 | plotlen = length(power); | |
29 | ||
30 | ber = zeros(1, plotlen); | |
31 | ||
32 | data = randi([0 M - 1], numSymbs, 1); | |
33 | modData = pskmod(data, M, pi / M, 'gray'); | |
34 | ||
35 | ||
36 | %% Chromatic dispersion | |
37 | D = 17; % ps / (nm km) | |
38 | lambda = 1550; % nm | |
39 | z = 600; % km | |
40 | ||
41 | ||
42 | for i = 1:plotlen | |
43 | snr = Es(i) / sps / N0; | |
44 | snr_dB = 10 * log10(snr); | |
45 | ||
46 | x = txFilter(modData, rolloff, span, sps); | |
47 | %% Now, sum(abs(x) .^ 2) / length(x) should be 1. | |
48 | %% We can set its power simply by multiplying. | |
49 | x = sqrt(power(i)) * x; | |
50 | ||
51 | %% We can now do split-step Fourier. | |
52 | gamma = 1.2; % watt^-1 / km | |
53 | %%stepnum = round(40 * z * gamma); % Nonlinear Fiber optics, App B | |
54 | stepnum = 100; | |
55 | xCD = splitstepfourier(x, D, lambda, z, Tsamp, gamma, stepnum); | |
56 | ||
57 | y = awgn(xCD, snr, power(i), 'linear'); | |
58 | %%y = xCD; | |
59 | ||
60 | r = rxFilter(y, rolloff, span, sps); | |
61 | rCDComp = CDCompensation(r, D, lambda, z, Tsamp); | |
62 | rCDComp = normalizeEnergy(rCDComp, numSymbs*sps, 1); | |
63 | ||
64 | rSampled = rCDComp(sps*span/2+1:sps:(numSymbs+span/2)*sps); | |
65 | rNoCompSampled = r(sps*span/2+1:sps:(numSymbs+span/2)*sps); | |
66 | ||
67 | %% rotate rNoCompSampled to match original data | |
68 | theta = angle(-sum(rNoCompSampled .^ M)) / M; | |
69 | %% if theta approx +pi/M, wrap to -pi/M | |
70 | if abs(theta - pi / M) / (pi / M) < 0.1 | |
71 | theta = -pi / M; | |
72 | end | |
73 | rNoCompSampled = rNoCompSampled .* exp(-j * theta); | |
74 | ||
75 | ||
76 | %% Not entirely sure why, but after using FFT instead of time-domain | |
77 | %% convolution for simulating CD, we now need to do the same rotation | |
78 | %% for rSampled as well, but this time with a positive rotation. | |
79 | theta = angle(-sum(rSampled .^ M)) / M; | |
80 | if abs(theta + pi / M) / (pi / M) < 0.1 | |
81 | theta = +pi / M; | |
82 | end | |
83 | rSampled = rSampled .* exp(-1j * theta); | |
84 | ||
85 | ||
86 | %% adaptive filter | |
87 | adaptFilterOut = adaptiveCMA(rSampled); | |
88 | ||
89 | demodAdapt = pskdemod(adaptFilterOut, M, pi / M, 'gray'); | |
90 | [~, ber(i)] = biterr(data, demodAdapt); | |
91 | end | |
92 | ||
93 | figure(1); | |
94 | clf; | |
95 | ||
96 | %% Plot simulated results | |
97 | semilogy(power_dBm, ber, 'Color', [0, 0.6, 0], 'LineWidth', 2); | |
98 | hold on; | |
99 | ||
100 | title({'CD + Kerr + CD compensation', ... | |
101 | strcat(['$D = 17$ ps/(nm km), $z = ', num2str(z), '$ km']), ... | |
102 | strcat(['$E_b/N_0 = ', num2str(N0ref_dB), '$ dB at 1 mW'])}); | |
103 | grid on; | |
104 | xlabel('Optical power (dBm)'); | |
105 | ylabel('BER'); | |
106 | ||
107 | formatFigure; |