目的

设计一个MO dulator / DEM odulator对准确地传送数据尽可能快地经模拟普通老式电话服务（POTS） 。

脚步

1. 生成一些随机（/dev/random或类似数据）的数据，将需要3-4秒来传输
2. 使用您的调制器调制数据以生成音频文件
3. 通过POTS模拟器传递音频文件。如果您没有Python / Scipy，则可以使用表单上传文件，或者发出JSON API请求。
4. 将音频文件解调回二进制数据
5. 验证输入和输出是否相等*（每1000位中的限制1个会损坏）
6. 得分是传输的位数除以音频文件的长度（位数/秒）

规则

• 输入文件必须为3-4秒，44.1 kHz，单声道。
• 以30 dB的SNR运行模拟器（默认设置）
• 解调器必须以不超过10 ^-3（每千位1个）的误码率重建传输的数据。
• 不允许数字压缩（即压缩数据。这超出了挑战的范围。）
• 请勿尝试将数据推入4 kHz以上的频率。（我的过滤器并不完美，但它们的抽头数量相对来说相当像POTS。）
• 如果您的调制解调器协议需要简短的前同步码（不超过1秒）来同步/校准接收器，则不会受到影响。
• 如果可能的话，请将音频文件存放在可访问的地方，以便我们听到嘟嘟声。

例

这是一个示例笔记本，通过简单的“开-关键控”（包括音频样本！）演示了调制/解调。

它将得分为100（位/秒）。请注意，它的发射信噪比差得多，为5 dB。

MATLAB，1960 bps

这是我更新的尝试：

fs = 44100; %44.1kHz audio rate
fc = 2450;  %2.45kHz carrier - nice fraction of fs!
fsym = fc/5; %symbol rate

tmax = 4; %about 4 seconds worth

preamblesyms = 6;

t = 1/fs:1/fs:(tmax+preamblesyms/fsym);

symbols = preamblesyms+fsym*tmax;
symbollength = length(t)/symbols;
bits = symbols*3;
bitstream = [zeros(1,preamblesyms*3),rand(1,bits-preamblesyms*3)>0.5]; %Add a little preamble of 18 bits
data = bin2dec(char(reshape(bitstream,3,symbols)'+'0'))';

greycode = [0 1 3 2 6 7 5 4];

%Encode the symbols using QAM8 - we use effectively grey code so that
%adjacent symbols in the constellation have only one bit difference
%(minimises error rate)
encoded = zeros(2,symbols);
encoded(1,data==1) = 1/sqrt(2);
encoded(1,data==3) = 1;
encoded(1,data==2) = 1/sqrt(2);
encoded(1,data==7) = -1/sqrt(2);
encoded(1,data==5) = -1;
encoded(1,data==4) = -1/sqrt(2);
encoded(2,data==0) = 1;
encoded(2,data==1) = 1/sqrt(2);
encoded(2,data==2) = -1/sqrt(2);
encoded(2,data==6) = -1;
encoded(2,data==7) = -1/sqrt(2);
encoded(2,data==4) = 1/sqrt(2);

%Modulate onto carrier
carrier = [sin(2*pi*fc*t);cos(2*pi*fc*t)];
signal = reshape(repmat(encoded(1,:)',1,symbollength)',1,[]);
signal(2,:) = reshape(repmat(encoded(2,:)',1,symbollength)',1,[]);
modulated = sum(signal.*carrier)';

%Write out an audio file
audiowrite('audio.wav',modulated,fs);

%Wait for the user to run through the POTS simulator
input('');

%Read in the filtered data
filtered=audioread('audio.pots-filtered.wav')';

%Recover the two carrier signals
preamblecos = filtered(symbollength+1:symbollength*2);
preamblesin = filtered(symbollength+1+round(symbollength*3/4):symbollength*2+round(symbollength*3/4));

%Replicated the recovered carriers for all symbols
carrierfiltered = [repmat(preamblesin,1,symbols);repmat(preamblecos,1,symbols)];

%Generate a demodulation filter (pass up to 0.66*fc, stop at 1.33*fc
%(really we just need to kill everything around 2*fc where the alias ends up)
d=fdesign.lowpass('Fp,Fst,Ap,Ast',0.05,0.1,0.5,60);
Hd = design(d,'equiripple');

%Demodulate the incoming stream
demodulated = carrierfiltered .* [filtered;filtered];
demodulated(1,:)=filtfilt(Hd.Numerator,1,demodulated(1,:));
demodulated(2,:)=filtfilt(Hd.Numerator,1,demodulated(2,:));

%Split signal up into bit periods
recovereddemodulated=[];
recovereddemodulated(1,:,:) = reshape(demodulated(1,:),symbollength,symbols);
recovereddemodulated(2,:,:) = reshape(demodulated(2,:),symbollength,symbols);

%Extract the average level for each bit period. Only look at the second
%half to account for slow rise times in the signal due to filtering
recoveredsignal=mean(recovereddemodulated(1,round(symbollength/2):symbollength,:));
recoveredsignal(2,:)=mean(recovereddemodulated(2,round(symbollength/2):symbollength,:));

%Convert the recovered signal into a complex number.
recoveredsignal=recoveredsignal(2,:) + 1j*recoveredsignal(1,:);

%Determine the magnitude and angle of the symbol. The phase is normalised
%to pi/4 as that is the angle between the symbols. Rounding this to the
%nearest integer will tell us which of the 8 phases it is closest to
recoveredphase = round(angle(recoveredsignal)/(pi/4));
recoveredphase = mod(recoveredphase+8,8)+1; %Remap to an index in the grey code vector.

%Determine the symbol in the QAM8 constellation
recoveredencoded=greycode(recoveredphase);
recoveredencoded(1:preamblesyms)=0; %Assume the preamble is correct for comparison

%Turn it back in to a bit stream
bitstreamRecovered = reshape(dec2bin(recoveredencoded)'-'0',1,[]);

%And check if they are all correct...
if(all(bitstream==bitstreamRecovered))
    disp(['Woop, ' num2str(fsym*4) 'bps']);
else
    error('Its corrupt Jim.');
end

自从第一次尝试以来，我已经玩了一些。现在在开头有一个小的前同步码（18位周期，但可能会更短），其中仅包含一个余弦波。我提取并复制了它，以创建正确相位的正弦和余弦载波进行解调-因为这是很短的序言，所以我没有按照您的指示将其计入比特率。

另外，自第一次尝试以来，我现在使用QAM8星座图来实现每个符号3位而不是2位。这实际上使传输速率加倍。因此，使用〜2.4kHz载波，我现在达到1960bps。

我还改进了符号检测，以使平均不会受到滤波引起的缓慢上升时间的影响-基本上，只有每个比特周期的后半部分被平均才能消除上升时间的影响。

从Shannon-Hartley理论（假设SNR为30dB）到40kbps理论信道带宽仍然相差甚远

对于那些喜欢恐怖声音的人，这是新条目：

如果有人感兴趣，这是以前的960bps条目