function varargout = FSK2(varargin)
% FSK2 MATLAB code for FSK2.fig
% FSK2, by itself, creates a new FSK2 or raises the existing
% singleton*.
%
% H = FSK2 returns the handle to a new FSK2 or the handle to
% the existing singleton*.
%
% FSK2(‘CALLBACK’,hObject,eventData,handles,…) calls the local
% function named CALLBACK in FSK2.M with the given input arguments.
%
% FSK2(‘Property’,‘Value’,…) creates a new FSK2 or raises the
% existing singleton*. Starting from the left, property value pairs are
% applied to the GUI before FSK2_OpeningFcn gets called. An
% unrecognized property name or invalid value makes property application
% stop. All inputs are passed to FSK2_OpeningFcn via varargin.
%
% *See GUI Options on GUIDE’s Tools menu. Choose “GUI allows only one
% instance to run (singleton)”.
%
% See also: GUIDE, GUIDATA, GUIHANDLES

% Edit the above text to modify the response to help FSK2

% Last Modified by GUIDE v2.5 15-Mar-2021 08:48:22

% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct(‘gui_Name’, mfilename, …
‘gui_Singleton’, gui_Singleton, …
‘gui_OpeningFcn’, @FSK2_OpeningFcn, …
‘gui_OutputFcn’, @FSK2_OutputFcn, …
‘gui_LayoutFcn’, [] , …
‘gui_Callback’, []);
if nargin && ischar(varargin{1})
gui_State.gui_Callback = str2func(varargin{1});
end

if nargout
[varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});
else
gui_mainfcn(gui_State, varargin{:});
end
% End initialization code - DO NOT EDIT

% — Executes just before FSK2 is made visible.
function FSK2_OpeningFcn(hObject, eventdata, handles, varargin)
% This function has no output args, see OutputFcn.
% hObject handle to figure
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% varargin command line arguments to FSK2 (see VARARGIN)

i=10;%基带信号码元数
j=500;
t=linspace(0,5,j);%0-5之间产生5000个点行矢量，即将[0,5]分成5000份
f1=10;%载波1频率
f2=5;%载波2频率
fs = j/5;
fm=i/5;%基带信号频率 码元数是10，而时域长度是5，也就是一个单位2个码元
a=round(rand(1,i));%产生随机序列

%产生基带信号
st1=t;
for n=1:10
if a(n)<1
for m=j/i*(n-1)+1:j/in
st1(m)=0;
end
else
for m=j/i(n-1)+1:j/i*n
st1(m)=1;
end
end
end

plot(handles.st1,t,st1,‘LineWidth’,1.5);
set(handles.st1,‘xtick’,[])
% title(‘基带信号st1’);
% axis([0,5,-1,2]);

%基带信号求反
st2=t;
for n=1:j
if st1(n)==1
st2(n)=0;
else
st2(n)=1;
end
end
% subplot(412);
% plot(t,st2);
% title(‘基带信号反码st2’);
% axis([0,5,-1,2]);

%载波信号
s1=cos(2pif1t);
s2=cos(2pif2t);
% plot(handles.s1,s1);
% title(‘载波信号s1’);
% plot(handles.s2,s2);
% title(‘载波信号s2’);

%调制
F1=st1.s1;%加入载波1
F2=st2.s2;%加入载波2
% figure(2);
% subplot(411);
% plot(t,F1);
% title('F1=s1st1’);
% subplot(412);
% plot(t,F2);
% title('F2=s2st2’);
e_fsk=F1+F2;
% subplot(413);
plot(handles.e_fsk,t,e_fsk);
set(handles.e_fsk,‘xtick’,[])
% title(‘2FSK信号’);%键控法产生的信号在相邻码元之间相位不一定连续

%加噪
nosie=rand(1,j);
fsk=e_fsk+nosie;
% subplot(414);
% plot(t,fsk);
% title(‘加噪声后信号’)

%相干解调
st1=fsk.s1; %与载波1相乘
[f,sf1] = T2F(t,st1);%傅里叶变换
[t,st1] = lpf(f,sf1,2fm);%通过低通滤波器
% figure(3);
% subplot(311);
% plot(t,st1);
% title(‘加噪后的信号与s1相乘后波形’);
st2=fsk.s2;%与载波2相乘
[f,sf2] = T2F(t,st2);%通过低通滤波器
[t,st2] = lpf(f,sf2,2fm);
% subplot(312);
% plot(t,st2);
% title(‘加噪后的信号与s2相乘后波形’);

%抽样判决
for m=0:i-1
if st1(1,m50+25)>st2(1,m50+25)
for j=m*50+1:(m+1)50
at(1,j)=1;
end
else
for j=m50+1:(m+1)*50
at(1,j)=0;
end
end
end
% subplot(313);
plot(handles.at,t,at,‘LineWidth’,1.5);
set(handles.at,‘xtick’,[])
% axis([0,5,-1,2]);
% title(‘抽样判决后波形’)

fft_st1=abs(fft(st1)/j);
fft_st1_1 = fft_st1(1:j/2+1);
fft_st1_1(2:end-1) = 2fft_st1_1(2:end-1);
f_x = fs(0:(j/2))/j;
plot(handles.axes10, f_x,fft_st1_1);
set(handles.axes10,‘ylim’,[0 0.5])

fft_y=abs(fft(fsk)/j);
fft_y_1 = fft_y(1:j/2+1);
fft_y_1(2:end-1) = 2fft_y_1(2:end-1);
f_x = fs(0:(j/2))/j;
plot(handles.axes12, f_x,fft_y_1);

fft_at=abs(fft(at)/j);
fft_at_1 = fft_at(1:j/2+1);
fft_at_1(2:end-1) = 2fft_at_1(2:end-1);
f_x = fs(0:(j/2))/j;
plot(handles.axes14, f_x,fft_at_1);
set(handles.axes14,‘ylim’,[0 0.5])

% Choose default command line output for FSK2
handles.output = hObject;

% Update handles structure
guidata(hObject, handles);

% UIWAIT makes FSK2 wait for user response (see UIRESUME)
% uiwait(handles.figure1);

% — Outputs from this function are returned to the command line.
function varargout = FSK2_OutputFcn(hObject, eventdata, handles)
% varargout cell array for returning output args (see VARARGOUT);
% hObject handle to figure
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)

% Get default command line output from handles structure
varargout{1} = handles.output;

T2F
function [f,sf]= T2F(t,st)
%利用FFT计算信号的频谱并与信号的真实频谱的抽样比较。
%脚本文件T2F.m定义了函数T2F，计算信号的傅立叶变换。
%Input is the time and the signal vectors,the length of time must greater
%than 2
%Output is the frequency and the signal spectrum
dt = t(2)-t(1);
T=t(end);
df = 1/T;
N = length(st);
f=-N/2df : df : N/2df-df;
sf = fft(st);
sf = T/N*fftshift(sf);

F2T
function [t,st]=F2T(f,sf)
%脚本文件F2T.m定义了函数F2T，计算信号的反傅立叶变换。
%This function calculate the time signal using ifft function for the input
df = f(2)-f(1);
Fmx = ( f(end)-f(1) +df);
dt = 1/Fmx;
N = length(sf);
T = dtN;
%t=-T/2:dt:T/2-dt;
t = 0:dt:T-dt;
sff = fftshift(sf);
st = Fmxifft(sff);

LPF
function [t,st]=lpf(f,sf,B)
%This function filter an input data using a lowpass filter
%Inputs: f: frequency samples
% sf: input data spectrum samples
% B: lowpass bandwidth with a rectangle lowpass
%Outputs: t: time samples
% st: output data time samples
df = f(2)-f(1);
T = 1/df;
hf = zeros(1,length(f));%全零矩阵
bf = [-floor( B/df ): floor( B/df )] + floor( length(f)/2 );
hf(bf)=1;
yf=hf.*sf;
[t,st]=F2T(f,yf);
st = real(st);

        实现二进制数字调制与解调信号的仿真是我的MATLAB课程设计的一部分，我参考了网上的一些资料，并加入了一些自己的想法，代码已在本地MATLAB编译通过且能正常运行

       2ASK——二进制振幅键控

i=10;%10个码元
j=5000;
t=linspace(0,5,j);%0-5之间产生5000个点行矢量，即将[0,5]分成5000份
fc=10;%载波频率
fm=i/5;%码元速率
%产生基带信号
x=(rand(1,i));%rand函数产生在0-1之间随机数，共1-10个
%figure(2)l;plot(x);
a=round(x);%随机序列，round取最接近小数的整数
%>0.5的值就为1，<0.5的值就为0
%figure(3);stem(a);%火柴梗状图

st=t;
for n=1:10
    if a(n)<1
        disp(j/i*(n-1))
        for m=j/i*(n-1)+1:j/i*n  %a(1)是1的话,就将0-1赋值为1
            st(m)=0;
        end
    else
        for m=j/i*(n-1)+1:j/i*n
            st(m)=1;
        end
    end
end
figure(1);
subplot(421);
plot(t,st);

axis([0,5,-1,2]);
title('基带信号st');
%载波
s1=cos(2*pi*fc*t);
subplot(422);
plot(s1);
title('载波信号s1');

%调制
e_2ask=st.*s1;%st是基带信号,s1是载波
subplot(423);
plot(t,e_2ask);
title('已调信号');

noise =rand(1,j);
e_2ask=e_2ask+noise;%加入噪声
subplot(424);
plot(t,e_2ask);
title('加入噪声的信号');

%相干解调
at=e_2ask.*cos(2*pi*fc*t);%这里用的cos必须和载波s1完全同步
%subplot(428);plot(t,at);
at=at-mean(at);%因为是单极性波形，还有直流分量，应去掉
subplot(425);
plot(t,at);
title('与载波相乘后信号');

[f,af] = T2F(t,at);%通过低通滤波器
[t,at] = lpf(f,af,2*fm);
subplot(426);
plot(t,at);
title('相干解调后波形');

%抽样判决
for m=0:i-1 %i=10   i是码元个数
    if (at(1,m*500+250)+0.5)<0.5%500是1个码元的长度，+250就是正好每次都定位到每个码元中部
        for j=m*500+1:(m+1)*500%如果判决这位码元的值<0.5,那么这个码元判为0
            at(1,j)=0;
        end
    else
        for j=m*500+1:(m+1)*500
            at(1,j)=1;%否则判为1
        end
    end
end
subplot(427);
plot(t,at);
axis([0,5,-1,2]);
title('抽样判决后波形')

用到的函数

①T2F.m

function [f,sf]= T2F(t,st)
%利用FFT计算信号的频谱并与信号的真实频谱的抽样比较。
%脚本文件T2F.m定义了函数T2F，计算信号的傅立叶变换。
%Input is the time and the signal vectors,the length of time must greater
%than 2
%Output is the frequency and the signal spectrum
dt = t(2)-t(1);
T=t(end);
df = 1/T;
N = length(st);
f=-N/2*df : df : N/2*df-df;
sf = fft(st);
sf = T/N*fftshift(sf);

②F2T.m

function [t,st]=F2T(f,sf)
%脚本文件F2T.m定义了函数F2T，计算信号的反傅立叶变换。
%This function calculate the time signal using ifft function for the input
df = f(2)-f(1);
Fmx = ( f(end)-f(1) +df);
dt = 1/Fmx;
N = length(sf);
T = dt*N;
%t=-T/2:dt:T/2-dt;
t = 0:dt:T-dt;
sff = fftshift(sf);
st = Fmx*ifft(sff);

③lpf.m

function [t,st]=lpf(f,sf,B)
%This function filter an input data using a lowpass filter
%Inputs: f: frequency samples
% sf: input data spectrum samples
% B: lowpass bandwidth with a rectangle lowpass
%Outputs: t: time samples
% st: output data time samples
df = f(2)-f(1);
T = 1/df;
hf = zeros(1,length(f));%全零矩阵
bf = [-floor( B/df ): floor( B/df )] + floor( length(f)/2 );
hf(bf)=1;
yf=hf.*sf;
[t,st]=F2T(f,yf);
st = real(st);

 

        实现二进制数字调制与解调信号的仿真是我的MATLAB课程设计的一部分，我参考了网上的一些资料，并加入了一些自己的想法，代码已在本地MATLAB编译通过且能正常运行

       2FSK——二进制频移键控

i=10;%基带信号码元数
j=5000;
t=linspace(0,5,j);%0-5之间产生5000个点行矢量，即将[0,5]分成5000份
f1=10;%载波1频率
f2=5;%载波2频率
fm=i/5;%基带信号频率    码元数是10，而时域长度是5，也就是一个单位2个码元
a=round(rand(1,i));%产生随机序列

%产生基带信号
st1=t;
for n=1:10
    if a(n)<1
        for m=j/i*(n-1)+1:j/i*n
            st1(m)=0;
        end
    else
        for m=j/i*(n-1)+1:j/i*n
            st1(m)=1;
        end
    end
end

figure(1);
subplot(411);
plot(t,st1);
title('基带信号st1');
axis([0,5,-1,2]);

%基带信号求反
st2=t;
for n=1:j
    if st1(n)==1
        st2(n)=0;
    else
        st2(n)=1;
    end
end
subplot(412);
plot(t,st2);
title('基带信号反码st2');
axis([0,5,-1,2]);

%载波信号
s1=cos(2*pi*f1*t);
s2=cos(2*pi*f2*t);
subplot(413),plot(s1);
title('载波信号s1');
subplot(414),plot(s2);
title('载波信号s2');

%调制
F1=st1.*s1;%加入载波1
F2=st2.*s2;%加入载波2
figure(2);
subplot(411);
plot(t,F1);
title('F1=s1*st1');
subplot(412);
plot(t,F2);
title('F2=s2*st2');
e_fsk=F1+F2;
subplot(413);
plot(t,e_fsk);
title('2FSK信号');%键控法产生的信号在相邻码元之间相位不一定连续

%加噪
nosie=rand(1,j);
fsk=e_fsk+nosie;
subplot(414);
plot(t,fsk);
title('加噪声后信号')

%相干解调
st1=fsk.*s1; %与载波1相乘
[f,sf1] = T2F(t,st1);%傅里叶变换
[t,st1] = lpf(f,sf1,2*fm);%通过低通滤波器
figure(3);
subplot(311);
plot(t,st1);
title('加噪后的信号与s1相乘后波形');
st2=fsk.*s2;%与载波2相乘
[f,sf2] = T2F(t,st2);%通过低通滤波器
[t,st2] = lpf(f,sf2,2*fm);
subplot(312);
plot(t,st2);
title('加噪后的信号与s2相乘后波形');

%抽样判决
for m=0:i-1
    if st1(1,m*500+250)>st2(1,m*500+250)
        for j=m*500+1:(m+1)*500
            at(1,j)=1;
        end
    else
        for j=m*500+1:(m+1)*500
            at(1,j)=0;
        end
    end
end
subplot(313);
plot(t,at);
axis([0,5,-1,2]);
title('抽样判决后波形')

用到的函数

①T2F.m

function [f,sf]= T2F(t,st)
%利用FFT计算信号的频谱并与信号的真实频谱的抽样比较。
%脚本文件T2F.m定义了函数T2F，计算信号的傅立叶变换。
%Input is the time and the signal vectors,the length of time must greater
%than 2
%Output is the frequency and the signal spectrum
dt = t(2)-t(1);
T=t(end);
df = 1/T;
N = length(st);
f=-N/2*df : df : N/2*df-df;
sf = fft(st);
sf = T/N*fftshift(sf);

②F2T.m

function [t,st]=F2T(f,sf)
%脚本文件F2T.m定义了函数F2T，计算信号的反傅立叶变换。
%This function calculate the time signal using ifft function for the input
df = f(2)-f(1);
Fmx = ( f(end)-f(1) +df);
dt = 1/Fmx;
N = length(sf);
T = dt*N;
%t=-T/2:dt:T/2-dt;
t = 0:dt:T-dt;
sff = fftshift(sf);
st = Fmx*ifft(sff);

③lpf.m

function [t,st]=lpf(f,sf,B)
%This function filter an input data using a lowpass filter
%Inputs: f: frequency samples
% sf: input data spectrum samples
% B: lowpass bandwidth with a rectangle lowpass
%Outputs: t: time samples
% st: output data time samples
df = f(2)-f(1);
T = 1/df;
hf = zeros(1,length(f));%全零矩阵
bf = [-floor( B/df ): floor( B/df )] + floor( length(f)/2 );
hf(bf)=1;
yf=hf.*sf;
[t,st]=F2T(f,yf);
st = real(st);