Commit | Line | Data |
---|---|---|
5fae0077 AIL |
1 | numSymbs = 2^16; |
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 = 8; % 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 | power_dBm = -6:1:4; | |
17 | %%power_dBm = 0; | |
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 | %% At current settings, N0 = 0.002 pJ | |
27 | ||
28 | plotlen = length(power); | |
29 | ||
30 | ber = zeros(1, plotlen); | |
31 | ||
32 | data = randi([0 M - 1], numSymbs, 1); | |
33 | %%modData = dpskmod(data, M, 0, 'gray'); | |
34 | modData = pskmod(data, M, 0, 'gray'); | |
35 | for i = 2:numSymbs | |
36 | modData(i) = modData(i) * modData(i-1); | |
37 | end | |
38 | ||
39 | ||
40 | %% Chromatic dispersion | |
41 | D = 17; % ps / (nm km) | |
42 | lambda = 1550; % nm | |
43 | z = 100; % km | |
44 | ||
45 | ||
46 | linewidthTx = 0; % Hz | |
47 | linewidthLO = 1e6; % Hz | |
48 | ||
49 | ||
50 | TsampOrig = Tsamp; | |
51 | ||
52 | x_P1 = txFilter(modData, rolloff, span, sps); | |
53 | ||
54 | ||
55 | for i = 1:plotlen | |
56 | sps = 8; | |
57 | Tsamp = TsampOrig; | |
58 | ||
59 | snr = Es(i) / sps / N0; | |
60 | snr_dB = 10 * log10(snr); | |
61 | ||
62 | %%x = txFilter(modData, rolloff, span, sps); | |
63 | %% Now, sum(abs(x) .^ 2) / length(x) should be 1. | |
64 | %% We can set its power simply by multiplying. | |
65 | x = sqrt(power(i)) * x_P1; | |
66 | ||
67 | %% We can now do split-step Fourier. | |
68 | gamma = 1.2; % watt^-1 / km | |
69 | ||
70 | ||
71 | xCDKerr = splitstepfourier(x, D, lambda, z, Tsamp, gamma); | |
72 | ||
73 | xpn = phaseNoise(xCDKerr, linewidthTx, linewidthLO, Tsamp); | |
74 | ||
75 | y = awgn(xpn, snr_dB, 'measured', 'db'); | |
76 | %y = xCDKerr; | |
77 | ||
78 | r = rxFilter(y, rolloff, span, sps); | |
79 | sps = 2; | |
80 | Tsamp = Tsamp * 4; | |
81 | ||
82 | rCDComp = CDCompensation(r, D, lambda, z, Tsamp); | |
83 | rCDComp = normalizeEnergy(rCDComp, numSymbs * sps, 1); | |
84 | ||
85 | rSampled = rCDComp(2:2:end); | |
86 | ||
87 | %% adaptive filter | |
88 | [adaptFilterOut, convergeIdx] = adaptiveCMA(rSampled); | |
89 | ||
90 | pncorr = phaseNoiseCorr(adaptFilterOut, M, 0, 40).'; | |
91 | ||
92 | demodAdapt = pskdemod(pncorr, M, 0, 'gray'); | |
93 | remod = pskmod(demodAdapt, M, 0, 'gray'); | |
94 | delayed = [1; remod(1:end-1)]; | |
95 | demod = pskdemod(remod .* conj(delayed), M, 0, 'gray'); | |
96 | ||
97 | if convergeIdx < Inf | |
98 | [~, ber(i)] = biterr(data(convergeIdx:end), demod(convergeIdx:end)); | |
99 | else | |
100 | [~, ber(i)] = biterr... | |
101 | (data(ceil(0.8*numSymbs):end), ... | |
102 | demod(ceil(0.8*numSymbs):end)); | |
103 | end | |
104 | end | |
105 | ||
106 | ber | |
107 | ||
108 | ||
109 | figure(1); | |
110 | clf; | |
111 | ||
112 | %% Plot simulated results | |
113 | qp = 20 * log10(erfcinv(2*ber)*sqrt(2)); | |
114 | plot(power_dBm, qp, 'Color', [0, 0.6, 0], 'LineWidth', 2); | |
115 | hold on; | |
116 | ||
117 | title({'CD + Kerr + CD compensation', ... | |
118 | strcat(['$D = 17$ ps/(nm km), $z = ', num2str(z), '$ km'])}); | |
119 | grid on; | |
120 | xlabel('Optical power (dBm)'); | |
121 | ylabel('$20 \log_{10}\left(\sqrt{2}\mathrm{erfc}^{-1}(2 BER)\right)$'); | |
122 | ||
123 | formatFigure; |