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% fsk_lock_down.m
% David Rowe April 2020
%
% tests for "Lock down" waveform, low Eb/No 4FSK
fsk_lib;
% "Genie" (ie perfect) timing estimate, we just want to see impact on BER from frequency est errors
function rx_bits = simple_fsk_demod(states, rx, f)
M = states.M; Ts = states.Ts; Fs = states.Fs; N = states.nin;
nsymb = states.nin/states.Ts;
rx_filter = zeros(states.nin,M);
rx_symbols = zeros(nsymb,M);
% Down convert each tone. We can use any time index for down
% conversion as it's non-coherent
for m=1:M
phase = exp(-j*2*pi*(1:N)'*f(m)/Fs);
rx_filter(:,m) = rx .* phase;
end
% sum energy for each symbol
for s=1:nsymb
st_sym = (s-1)*Ts+1; en_sym = s*Ts;
for m=1:M
rx_symbols(s,m) = sum(rx_filter(st_sym:en_sym,m));
end
end
% map symbols back to bits
rx_bits = [];
for s=1:nsymb
[tone_max tone_index] = max(rx_symbols(s,:));
arx_bits = dec2bin(tone_index - 1, states.bitspersymbol) - '0';
rx_bits = [rx_bits arx_bits];
end
end
% set up "lock down" waveform
function [states M bits_per_frame] = lock_down_init(Rs,Fs,df,tx_tone_separation=250)
M = 4;
states = fsk_init(Fs,Rs,M,P=8,nsym=100);
bits_per_frame = 512;
states.tx_real = 0; % complex signal
states.tx_tone_separation = tx_tone_separation;
states.ftx = -2.5*states.tx_tone_separation + states.tx_tone_separation*(1:M);
states.fest_fmin = -Fs/2;
states.fest_fmax = +Fs/2;
states.df = df;
% cumulative PDF, cdf(x) probability of 0....x errors in frame
cdf = binocdf(1:bits_per_frame, bits_per_frame, 0.3);
% our valid frame threshold is 50% probability, so if we get this many errors
% we have a 50% chance it's a valid frame
nerrs_valid = find(cdf>=0.5)(1);
% our invalid frame threshold is 99% probability, so very unlikely to
% get this many errors
nerrs_invalid = find(cdf>=0.99)(1);
states.ber_valid_thresh = nerrs_valid/bits_per_frame;
states.ber_invalid_thresh = nerrs_invalid/bits_per_frame;
end
% run a test at an Eb/No point, measure how many dud freq estimates using both algorithms
function [states f_log f_log2 num_dud1 num_dud2 ber ber2] = freq_run_test(EbNodB = 10, num_frames=10, Fs=8000, Rs=100, df=0)
[states M bits_per_frame] = lock_down_init(Rs,Fs,df);
N = states.N;
EbNo = 10^(EbNodB/10);
variance = states.Fs/(states.Rs*EbNo*states.bitspersymbol);
nbits = bits_per_frame*num_frames;
tx_bits = round(rand(1,nbits));
tx = fsk_mod(states, tx_bits);
noise = sqrt(variance/2)*randn(length(tx),1) + j*sqrt(variance/2)*randn(length(tx),1);
rx = tx + noise;
run_frames = floor(length(rx)/N)-1;
st = 1; f_log = []; f_log2 = []; rx_bits = []; rx_bits2 = [];
for f=1:run_frames
% extract nin samples from input stream
nin = states.nin;
en = st + states.nin - 1;
% due to nin variations it's possible to overrun buffer
if en < length(rx)
sf = rx(st:en);
states = est_freq(states, sf, states.M);
arx_bits = simple_fsk_demod(states, sf, states.f);
rx_bits = [rx_bits arx_bits];
arx_bits = simple_fsk_demod(states, sf, states.f2);
rx_bits2 = [rx_bits2 arx_bits];
f_log = [f_log; states.f]; f_log2 = [f_log2; states.f2];
st += nin;
end
end
% ignore start up transient
startup = 1; % TODO make this sensible/proportional so its scales across Rs
if num_frames > startup
tx_bits = tx_bits(startup*bits_per_frame:end);
rx_bits = rx_bits(startup*bits_per_frame:end);
rx_bits2 = rx_bits2(startup*bits_per_frame:end);
end
% measure BER
nerrors = sum(xor(tx_bits(1:length(rx_bits)),rx_bits)); ber = nerrors/nbits;
nerrors2 = sum(xor(tx_bits(1:length(rx_bits2)),rx_bits2)); ber2 = nerrors2/nbits;
% Lets say that for a valid freq estimate, all four tones must be within 0.1*Rs of their tx frequency
num_dud1 = 0; num_dud2 = 0;
for i=1:length(f_log)
if sum(abs(f_log(i,:)-states.ftx) > 0.1*states.Rs)
num_dud1++;
end
if sum(abs(f_log2(i,:)-states.ftx) > 0.1*states.Rs)
num_dud2++;
end
end
end
function freq_run_single(EbNodB = 3, num_frames = 10)
[states f_log f_log2 num_dud1 num_dud2 ber ber2] = freq_run_test(EbNodB, num_frames);
percent_dud1 = 100*num_dud1/length(f_log);
percent_dud2 = 100*num_dud2/length(f_log);
printf("EbNodB: %4.2f dB tests: %3d duds1: %3d %5.2f %% duds2: %3d %5.2f %% ber1: %4.3f ber2: %4.3f\n",
EbNodB, length(f_log), num_dud1, percent_dud1, num_dud2, percent_dud2, ber, ber2)
figure(1); clf;
ideal=ones(length(f_log),1)*states.ftx;
plot((1:length(f_log)),ideal(:,1),'bk;ideal;')
hold on; plot((1:length(f_log)),ideal(:,2:states.M),'bk'); hold off;
hold on;
plot(f_log(:,1), 'linewidth', 2, 'b;peak;');
plot(f_log(:,2:states.M), 'linewidth', 2, 'b');
plot(f_log2(:,1),'linewidth', 2, 'r;mask;');
plot(f_log2(:,2:states.M),'linewidth', 2, 'r');
hold off;
xlabel('Time (frames)'); ylabel('Frequency (Hz)');
title(sprintf("EbNo = %4.2f dB", EbNodB));
print("fsk_freq_est_single.png", "-dpng")
figure(2); clf;
errors = (f_log - states.ftx)(:);
ind = find(abs(errors) < 100);
errors2 = (f_log2 - states.ftx)(:);
ind2 = find(abs(errors2) < 100);
if length(ind)
subplot(211); hist(errors(ind),50)
end
if length(ind2)
subplot(212); hist(errors2(ind2),50)
end
end
% test peak and mask algorithms side by side
function freq_run_curve_peak_mask
EbNodB = 0:9;
m4fsk_ber_theory = [0.23 0.18 0.14 0.09772 0.06156 0.03395 0.01579 0.00591 0.00168 3.39E-4];
percent_log = []; ber_log = [];
for ne = 1:length(EbNodB)
[states f_log f_log2 num_dud1 num_dud2 ber ber2] = freq_run_test(EbNodB(ne), 10);
percent_dud1 = 100*num_dud1/length(f_log);
percent_dud2 = 100*num_dud2/length(f_log);
percent_log = [percent_log; [percent_dud1 percent_dud2]];
ber_log = [ber_log; [ber ber2]];
printf("EbNodB: %4.2f dB tests: %3d duds1: %3d %5.2f %% duds2: %3d %5.2f %% ber1: %4.3f ber2: %4.3f\n",
EbNodB(ne), length(f_log), num_dud1, percent_dud1, num_dud2, percent_dud2, ber, ber2)
end
figure(1); clf; plot(EbNodB, percent_log(:,1), 'linewidth', 2, '+-;peak;'); grid;
hold on; plot(EbNodB, percent_log(:,2), 'linewidth', 2, 'r+-;mask;'); hold off;
xlabel('Eb/No (dB)'); ylabel('% Errors');
title(sprintf("Fs = %d Rs = %d df = %3.2f", states.Fs, states.Rs, states.df));
print("fsk_freq_est_errors.png", "-dpng")
figure(2); clf; semilogy(EbNodB, m4fsk_ber_theory, 'linewidth', 2, 'bk+-;theory;'); grid;
hold on; semilogy(EbNodB, ber_log(:,1), 'linewidth', 2, '+-;peak;');
semilogy(EbNodB, ber_log(:,2), 'linewidth', 2, 'r+-;mask;'); hold off;
xlabel('Eb/No (dB)'); ylabel('BER');
title(sprintf("Fs = %d Rs = %d df = %3.2f", states.Fs, states.Rs, states.df));
print("fsk_freq_est_ber.png", "-dpng")
end
function freq_run_curve_mask(Fs,Rs)
EbNodB = 0:9;
m4fsk_ber_theory = [0.23 0.18 0.14 0.09772 0.06156 0.03395 0.01579 0.00591 0.00168 3.39E-4];
figure(1); clf; semilogy(EbNodB, m4fsk_ber_theory, 'linewidth', 2, 'bk+-;theory;'); grid;
xlabel('Eb/No (dB)'); ylabel('BER');
title(sprintf("Mask: Fs = %d Hz Rs = %d Hz", Fs, Rs));
hold on;
for df=-0.01:0.01:0.01
ber_log = [];
for ne = 1:length(EbNodB)
[states f_log f_log2 num_dud1 num_dud2 ber ber2] = freq_run_test(EbNodB(ne), 100, Fs, Rs, df*Rs);
ber_log = [ber_log; [ber ber2]];
printf("Fs: %d Rs: %d df %3.2f EbNodB: %4.2f dB tests: %3d ber: %4.3f\n",
Fs, Rs, df, EbNodB(ne), length(f_log), ber2)
end
semilogy(EbNodB, ber_log(:,2), 'linewidth', 2, sprintf("+-;df=% 3.2f Hz/s;",df*Rs));
end
hold off;
print(sprintf("fsk_freq_est_ber_%d_%d.png",Fs,Rs), "-dpng")
end
% Run a complete modem (freq and timing estimators running) at a
% single Eb/No point. At low Eb/No the estimators occasionally fall
% over so we get complete junk, we consider that case a packet error
% and exclude it from the BER estimation.
function [states ber per] = modem_run_test(EbNodB = 10, num_frames=10, Fs=8000, Rs=100, df=0, plots=0, spreadHz=0,tx_tone_separation=250)
[states M bits_per_frame] = lock_down_init(Rs, Fs, df, tx_tone_separation);
N = states.N;
if plots; states.verbose = 0x4; end
EbNo = 10^(EbNodB/10);
variance = states.Fs/(states.Rs*EbNo*states.bitspersymbol);
nbits = bits_per_frame*num_frames;
test_frame = round(rand(1,bits_per_frame)); tx_bits = [];
for f=1:num_frames
tx_bits = [tx_bits test_frame];
end
tx = fsk_mod(states, tx_bits);
noise = sqrt(variance/2)*randn(length(tx),1) + j*sqrt(variance/2)*randn(length(tx),1);
if spreadHz
% just use phase part of doppler spread, not interested in amplitude fading
spread = doppler_spread(spreadHz, Fs, round(1.1*length(tx)));
spread = exp(j*arg(spread(1:length(tx))));
rx = tx.*rot90(spread) + noise;
else
rx = tx + noise;
end
run_frames = floor(length(rx)/N)-1;
st = 1; f_log = []; f_log2 = []; rx_bits = []; rx_bits2 = [];
for f=1:run_frames
% extract nin samples from input stream
nin = states.nin;
en = st + states.nin - 1;
% due to nin variations it's possible to overrun buffer
if en < length(rx)
sf = rx(st:en);
states = est_freq(states, sf, states.M); states.f = states.f2;
[arx_bits states] = fsk_demod(states, sf);
rx_bits = [rx_bits arx_bits];
f_log = [f_log; states.f];
st += nin;
end
end
num_frames=floor(length(rx_bits)/bits_per_frame);
log_nerrs = []; num_frames_rx = 0;
for f=1:num_frames-1
st = (f-1)*bits_per_frame + 1; en = (f+1)*bits_per_frame;
states = ber_counter(states, test_frame, rx_bits(st:en));
log_nerrs = [log_nerrs states.nerr];
if states.ber_state; num_frames_rx++; end
end
if states.Terrs
printf("Fs: %d Rs: %d df % 3.2f sp: %2.1f EbNo: %4.2f ftx: %3d frx: %3d nbits: %4d nerrs: %3d ber: %4.3f\n",
Fs, Rs, df, spreadHz, EbNodB, num_frames, num_frames_rx, states.Tbits, states.Terrs, states.Terrs/states.Tbits);
ber = states.Terrs/states.Tbits;
else
ber = 0.5;
end
if plots
figure(1); clf;
ideal=ones(length(f_log),1)*states.ftx;
plot((1:length(f_log)),ideal(:,1),'bk;ideal;')
hold on; plot((1:length(f_log)),ideal(:,2:states.M),'bk'); hold off;
hold on;
plot(f_log(:,1), 'linewidth', 2, 'b;peak;');
plot(f_log(:,2:states.M), 'linewidth', 2, 'b');
hold off;
xlabel('Time (frames)'); ylabel('Frequency (Hz)');
figure(2); clf; plot(log_nerrs); title('Errors per frame');
end
per = 1 - num_frames_rx/num_frames;
end
% run BER v Eb/No curves over a range of frequency rate/change
function modem_run_curve(Fs, Rs, num_frames=100, dfmax=0.01)
EbNodB = 0:9;
m4fsk_ber_theory = [0.23 0.18 0.14 0.09772 0.06156 0.03395 0.01579 0.00591 0.00168 3.39E-4];
figure(1); clf; semilogy(EbNodB, m4fsk_ber_theory, 'linewidth', 2, 'bk+-;theory;'); grid;
xlabel('Eb/No (dB)'); ylabel('BER');
title(sprintf("Mask: Fs = %d Hz Rs = %d Hz", Fs, Rs)); hold on;
figure(2); clf;
xlabel('Eb/No (dB)'); ylabel('PER'); title(sprintf("Mask: Fs = %d Hz Rs = %d Hz", Fs, Rs));
grid; axis([min(EbNodB) max(EbNodB) 0 1]); hold on;
for df=-dfmax:dfmax:dfmax
ber_log = []; per_log = [];
for ne = 1:length(EbNodB)
[states ber per] = modem_run_test(EbNodB(ne), num_frames, Fs, Rs, df*Rs);
ber_log = [ber_log; ber]; per_log = [per_log; per];
end
figure(1); semilogy(EbNodB, ber_log, 'linewidth', 2, sprintf("+-;df=% 3.2f Hz/s;",df*Rs));
figure(2); plot(EbNodB, per_log, 'linewidth', 2, sprintf("+-;df=% 3.2f Hz/s;",df*Rs));
end
figure(1); hold off; print(sprintf("fsk_modem_ber_%d_%d.png",Fs,Rs), "-dpng")
figure(2); hold off; print(sprintf("fsk_modem_per_%d_%d.png",Fs,Rs), "-dpng")
end
% run BER v Eb/No curve with some phase noise spreading the energy of the tones in frequency
function modem_run_curve_spread(Fs, Rs, num_frames=100)
EbNodB = 0:9;
m4fsk_ber_theory = [0.23 0.18 0.14 0.09772 0.06156 0.03395 0.01579 0.00591 0.00168 3.39E-4];
figure(1); clf; semilogy(EbNodB, m4fsk_ber_theory, 'linewidth', 2, 'bk+-;theory;'); grid;
xlabel('Eb/No (dB)'); ylabel('BER');
title(sprintf("Spread: Fs = %d Hz Rs = %d Hz", Fs, Rs)); hold on;
figure(2); clf;
xlabel('Eb/No (dB)'); ylabel('PER');
title(sprintf("Spread: Fs = %d Hz Rs = %d Hz", Fs, Rs));
grid; axis([min(EbNodB) max(EbNodB) 0 1]); hold on;
spreadHz = [0.0 1 2 5];
for ns = 1:length(spreadHz)
ber_log = []; per_log = [];
for ne = 1:length(EbNodB)
[states ber per] = modem_run_test(EbNodB(ne), num_frames, Fs, Rs, 0, 0, spreadHz(ns));
ber_log = [ber_log; ber]; per_log = [per_log; per];
end
figure(1); semilogy(EbNodB, ber_log, 'linewidth', 2, sprintf("+-;spread=% 3.2f Hz;",spreadHz(ns)));
figure(2); plot(EbNodB, per_log, 'linewidth', 2, sprintf("+-;spread=% 3.2f Hz;",spreadHz(ns)));
end
figure(1); hold off; print(sprintf("fsk_modem_ber_spread_%d_%d.png",Fs,Rs), "-dpng")
figure(2); hold off; print(sprintf("fsk_modem_per_spread_%d_%d.png",Fs,Rs), "-dpng")
end
% study code rate versus Rs and MDS
function code_rate_table
packet_duration_sec = 20;
k = 256;
noise_figure = 1;
bits_per_symbol = 2;
noise_bandwidth = 3000;
code_rate=[1 0.8 0.5 1/3];
raw_ber=[2E-3 0.04 0.08 0.16];
EbNodB_4fsk=[8 4.5 3.5 1.5];
printf("Code Rate | Raw BER | 4FSK Eb/No | n,k | Rs | SNR | MDS |\n");
printf("| --- | --- | --- | --- | --- | --- | --- |\n");
for i=1:length(code_rate)
n = k/code_rate(i);
Rb = n/packet_duration_sec;
Rs = Rb/bits_per_symbol;
snr = EbNodB_4fsk(i) + 10*log10(Rb/noise_bandwidth);
mds = EbNodB_4fsk(i) + 10*log10(Rb) + noise_figure - 174;
printf("%3.2f | %4.3f | %2.1f | %d,%d | %4.1f | %4.1f | %5.1f |\n",
code_rate(i), raw_ber(i), EbNodB_4fsk(i), n, k, Rs, snr, mds);
end
end
graphics_toolkit("gnuplot");
more off;
% same results every time
rand('state',1);
randn('state',1);
% freq estimator tests (choose one)
#freq_run_single(3,10)
#freq_run_curve_peak_mask
#freq_run_curve_mask(8000,100)
#freq_run_curve_mask(24000,25)
#freq_run_curve_mask(8000,25)
% complete modem tests (choose one)
#modem_run_curve(24000,25,100)
#modem_run_curve(8000,100,50,0.05)
#modem_run_curve_spread(8000,25,50)
#modem_run_curve(8000,100,20)
modem_run_test(2, 20, 8000, 25, 0, 1, 0, 270);
% just print a table of code rates
#code_rate_table
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