bpskmatlab代码（bpsk调制及解调matlab）

今天给各位分享bpskmatlab代码的知识，其中也会对bpsk调制及解调matlab进行解释，如果能碰巧解决你现在面临的问题，别忘了关注本站，现在开始吧！

本文目录一览：

• 1、Matlab编写BPSK信号通过AWGN信道的仿真过程
• 2、用matlab进行BPSK调制和解调的仿真
• 3、几个问题关于Matlab编写BPSK信号通过AWGN信道的仿真(在线跪求大神，不胜感激)！！！
• 4、matlab编程实现最大似然解调 采用BPSK调制 并画出误码率曲线
• 5、matlab高手请支援

Matlab编写BPSK信号通过AWGN信道的仿真过程

主程序部分：

%programm 3-1

%bpsk.m

%

% Simulation program to realize BPSK transmission system

%

% Programmed by H.Harada and T.Yamamura,

%

%******************** Preparation part **********************

sr=256000.0; % Symbol rate

ml=1; % Number of modulation levels

br=sr.*ml; % Bit rate (=symbol rate in this case)

nd = 1000; % Number of symbols that simulates in each loop

ebn0=3; % Eb/N0

IPOINT=8; % Number of oversamples

%******************* Filter initialization ********************

irfn=21; % Number of filter taps

alfs=0.5; % Rolloff factor

[xh] = hrollfcoef(irfn,IPOINT,sr,alfs,1); %Transmitter filter coefficients

[xh2] = hrollfcoef(irfn,IPOINT,sr,alfs,0); %Receiver filter coefficients

%******************** START CALCULATION *********************

nloop=100; % Number of simulation loops

noe = 0; % Number of error data

nod = 0; % Number of transmitted data

for iii=1:nloop

%******************** Data generation ***********************

data=rand(1,nd)0.5; % rand: built in function

%******************** BPSK Modulation ***********************

data1=data.*2-1;

data2 = oversamp( data1, nd , IPOINT) ;

data3 = conv(data2,xh); % conv: built in function

%****************** Attenuation Calculation *****************

spow=sum(data3.*data3)/nd;

attn=0.5*spow*sr/br*10.^(-ebn0/10);

attn=sqrt(attn);

%********************** Fading channel **********************

% Generated data are fed into a fading simulator

% In the case of BPSK, only Ich data are fed into fading counter

% [ifade,qfade]=sefade(data3,zeros(1,length(data3)),itau,dlvl,th1,n0,itnd1,now1,length(data3),tstp,fd,flat);

% Updata fading counter

%itnd1 = itnd1+ itnd0;

%************ Add White Gaussian Noise (AWGN) ***************

inoise=randn(1,length(data3)).*attn; % randn: built in function

data4=data3+inoise;

data5=conv(data4,xh2); % conv: built in function

sample=irfn*IPOINT+1;

data6 = data5(sample:8:8*nd+sample-1);

%******************** BPSK Demodulation *********************

demodata=data6 0;

%******************** Bit Error Rate (BER) ******************

noe2=sum(abs(data-demodata)); % sum: built in function

nod2=length(data); % length: built in function

noe=noe+noe2;

nod=nod+nod2;

fprintf('%d\t%e\n',iii,noe2/nod2); %fprintf:built in function

end % for iii=1:nloop

%********************** Output result ***********************

ber = noe/nod;

fprintf('%d\t%d\t%d\t%e\n',ebn0,noe,nod,noe/nod);

%******************** end of file ***************************

下面是子程序：

% Program 3-2

% oversamp.m

%

% Insert zero data to input data

%

% Programmed by H.Harada

%

function [out] = oversamp( indata, nsymb , sample)

%****************** variables *************************

% indata : input sequence

% nsymb : Number of symbols

% sample : Number of oversample

% *****************************************************

out=zeros(1,nsymb*sample);

out(1:sample:1+sample*(nsymb-1))=indata;

%******************** end of file ***************************

子程序：

% Program 3-3

% hrollfcoef.m

%

% Generate coefficients of Nyquist filter

%

% programmed by H.Harada

%

function [xh] = hrollfcoef(irfn,ipoint,sr,alfs,ncc)

%****************** variables *************************

% irfn : Number of symbols to use filtering

% ipoint : Number of samples in one symbol

% sr : symbol rate

% alfs : rolloff coeficiense

% ncc : 1 -- transmitting filter 0 -- receiving filter

% *****************************************************

xi=zeros(1,irfn*ipoint+1);

xq=zeros(1,irfn*ipoint+1);

point = ipoint;

tr = sr ;

tstp = 1.0 ./ tr ./ ipoint;

n = ipoint .* irfn;

mid = ( n ./ 2 ) + 1;

sub1 = 4.0 .* alfs .* tr; % 4*alpha*R_s

for i = 1 : n

icon = i - mid;

ym = icon;

if icon == 0.0

xt = (1.0-alfs+4.0.*alfs./pi).* tr; % h(0)

else

sub2 =16.0.*alfs.*alfs.*ym.*ym./ipoint./ipoint;

if sub2 ~= 1.0

x1=sin(pi*(1.0-alfs)/ipoint*ym)./pi./(1.0-sub2)./ym./tstp;

x2=cos(pi*(1.0+alfs)/ipoint*ym)./pi.*sub1./(1.0-sub2);

xt = x1 + x2; % h(t) plot((1:length(xh)),xh)

else % (4alphaRst)^2 = 1plot((1:length(xh)),xh)

xt = alfs.*tr.*((1.0-2.0/pi).*cos(pi/4.0/alfs)+(1.0+2.0./pi).*sin(pi/4.0/alfs))./sqrt(2.0);

end % if sub2 ~= 1.0

end % if icon == 0.0

if ncc == 0 % in the case of receiver

xh( i ) = xt ./ ipoint ./ tr; % normalization

elseif ncc == 1 % in the case of transmitter

xh( i ) = xt ./ tr; % normalization

else

error('ncc error');

end % if ncc == 0

end % for i = 1 : n

%******************** end of file ***************************

就是这三个了，不知道能不能帮助你、、、

用matlab进行BPSK调制和解调的仿真

function output_frame = demodulation(input_modu, index)

% demodulation for IEEE802.11a

% Input: input_modu, complex values representing constellation points

% index

% Output: output_frame, output bit stream (data unit is one bit)

% In this version, increase the quatilization levels into 8.

% note: Matlab index starts from 1

Q_length=length(input_modu);

QAM_input_I = real(input_modu);

QAM_input_Q = imag(input_modu);

output_frame = zeros(1,length(input_modu)*index);

switch index

case 1,

BPSK_Demodu_I = [0 1]; %f(m)=(m+1)/2 + 1, so I=-1 --- 1, I=1 --- 2

idx = find(QAM_input_I1);

QAM_input_I(idx) = 1;

idx = find(QAM_input_I-1);

QAM_input_I(idx) = -1;

output_frame = BPSK_Demodu_I(round((QAM_input_I+1)/2) + 1);

case 2,

QPSK_Demodu_IQ = [0 1]; %f(m)=(m+1)/2 + 1, so I=-1 --- 1, I=1 --- 2

idx = find(QAM_input_I1);

QAM_input_I(idx) = 1;

idx = find(QAM_input_I-1);

QAM_input_I(idx) = -1;

idx = find(QAM_input_Q1);

QAM_input_Q(idx) = 1;

idx = find(QAM_input_Q-1);

QAM_input_Q(idx) = -1;

output_frame(1:2:end) = QPSK_Demodu_IQ(round((QAM_input_I+1)/2) + 1);

output_frame(2:2:end) = QPSK_Demodu_IQ(round((QAM_input_Q+1)/2) + 1);

case 3,

remapping=[0 0 0;0 0 1;0 1 0;0 1 1;1 0 0;1 0 1;1 1 0;1 1 1].';

for i=1:Q_length

phase_det=[2QAM_input_I(i)0QAM_input_Q(i) 0QAM_input_I(i)QAM_input_I(i)20QAM_input_Q(i) QAM_input_I(i)-20QAM_input_Q(i) -2QAM_input_I(i)QAM_input_I(i)00QAM_input_Q(i) QAM_input_I(i)-2QAM_input_Q(i)0 QAM_input_I(i)0-2QAM_input_I(i)QAM_input_Q(i)0 2QAM_input_I(i)QAM_input_Q(i)0 0QAM_input_I(i)QAM_input_I(i)2QAM_input_Q(i)0]

a=find(phase_det);

output_frame((1+(i-1)*3):(3+(i-1)*3))=remapping((1+(a-1)*3):(3+(a-1)*3));

end

case 4,

QAM_16_Demodu_IQ = [0 1 3 2]; %f(m)=(m+3)/2 + 1, so I=-3 --- 1, I=1 --- 3

idx = find(QAM_input_I3);

QAM_input_I(idx) = 3;

idx = find(QAM_input_I-3);

QAM_input_I(idx) = -3;

idx = find(QAM_input_Q3);

QAM_input_Q(idx) = 3;

idx = find(QAM_input_Q-3);

QAM_input_Q(idx) = -3;

tmp = round((QAM_input_I+3)/2) + 1;

output_frame(1:4:end) = bitget(QAM_16_Demodu_IQ(tmp),2);

output_frame(2:4:end) = bitget(QAM_16_Demodu_IQ(tmp),1);

tmp = round((QAM_input_Q+3)/2) + 1;

output_frame(3:4:end) = bitget(QAM_16_Demodu_IQ(tmp),2);

output_frame(4:4:end) = bitget(QAM_16_Demodu_IQ(tmp),1);

case 5,

remapping=[0 0 0 0 0;0 0 0 0 1;0 0 0 1 0;0 0 0 1 1;0 0 1 0 0;0 0 1 0 1;0 0 1 1 0;0 0 1 1 1;

0 1 0 0 0;0 1 0 0 1;0 1 0 1 0;0 1 0 1 1;0 1 1 0 0;0 1 1 0 1;0 1 1 1 0;0 1 1 1 1;

1 0 0 0 0;1 0 0 0 1;1 0 0 1 0;1 0 0 1 1;1 0 1 0 0;1 0 1 0 1;1 0 1 1 0;1 0 1 1 1;

1 1 0 0 0;1 1 0 0 1;1 1 0 1 0;1 1 0 1 1;1 1 1 0 0;1 1 1 0 1;1 1 1 1 0;1 1 1 1 1].';

for i=1:Q_length

phase_det=[4QAM_input_I(i)0QAM_input_Q(i)QAM_input_Q(i)2;2QAM_input_I(i)QAM_input_I(i)40QAM_input_Q(i)QAM_input_Q(i)2;0QAM_input_I(i)QAM_input_I(i)20QAM_input_Q(i)QAM_input_Q(i)2;4QAM_input_I(i)2QAM_input_Q(i)QAM_input_Q(i)4;

2QAM_input_I(i)QAM_input_I(i)42QAM_input_Q(i)QAM_input_Q(i)4;0QAM_input_I(i)QAM_input_I(i)22QAM_input_Q(i)QAM_input_Q(i)4;2QAM_input_I(i)QAM_input_I(i)44QAM_input_Q(i);0QAM_input_I(i)QAM_input_I(i)24QAM_input_Q(i);

QAM_input_I(i)-40QAM_input_Q(i)QAM_input_Q(i)2;-4QAM_input_I(i)QAM_input_I(i)-20QAM_input_Q(i)QAM_input_Q(i)2;-2QAM_input_I(i)QAM_input_I(i)00QAM_input_Q(i)QAM_input_Q(i)2;QAM_input_I(i)-42QAM_input_Q(i)QAM_input_Q(i)4;

-4QAM_input_I(i)QAM_input_I(i)-22QAM_input_Q(i)QAM_input_Q(i)4;-2QAM_input_I(i)QAM_input_I(i)02QAM_input_Q(i)QAM_input_Q(i)4;-4QAM_input_I(i)QAM_input_I(i)-24QAM_input_Q(i);-2QAM_input_I(i)QAM_input_I(i)04QAM_input_Q(i);

QAM_input_I(i)-4-2QAM_input_Q(i)QAM_input_Q(i)0;-4QAM_input_I(i)QAM_input_I(i)-2-2QAM_input_Q(i)QAM_input_Q(i)0;-2QAM_input_I(i)QAM_input_I(i)00QAM_input_Q(i)QAM_input_Q(i)0;QAM_input_I(i)-4-4QAM_input_Q(i)QAM_input_Q(i)-2;

-4QAM_input_I(i)QAM_input_I(i)-2-4QAM_input_Q(i)QAM_input_Q(i)-2;-2QAM_input_I(i)QAM_input_I(i)0-4QAM_input_Q(i)QAM_input_Q(i)-2;-4QAM_input_I(i)QAM_input_I(i)-2QAM_input_Q(i)-4;-2QAM_input_I(i)QAM_input_I(i)0QAM_input_Q(i)-4;

4QAM_input_I(i)-2QAM_input_Q(i)QAM_input_Q(i)0;2QAM_input_I(i)QAM_input_I(i)4-2QAM_input_Q(i)QAM_input_Q(i)0;0QAM_input_I(i)QAM_input_I(i)20QAM_input_Q(i)QAM_input_Q(i)0;4QAM_input_I(i)-4QAM_input_Q(i)QAM_input_Q(i)-2;

2QAM_input_I(i)QAM_input_I(i)4-4QAM_input_Q(i)QAM_input_Q(i)-2;0QAM_input_I(i)QAM_input_I(i)2-4QAM_input_Q(i)QAM_input_Q(i)-2;2QAM_input_I(i)QAM_input_I(i)4QAM_input_Q(i)-4;0QAM_input_I(i)QAM_input_I(i)2QAM_input_Q(i)-4];

a=find(phase_det);

output_frame((1+(i-1)*5):(5+(i-1)*5))=remapping((1+(a-1)*5):(5+(a-1)*5));

end %5+i 3+i 1+i 5+3*i 3+3*i 1+3*i 3+5*i 1+5*i -5+i -3+i -1+i -5+3*i -3+3*i -1+3*i -3+5*i -1+5*i -5-i -3-i -1-i -5-3*i -3-3*i -1-3*i -3-5*i -1-5*i 5-i 3-i 1-i 5-3*i 3-3*i 1-3*i 3-5*i 1-5*i

case 6,

QAM_64_Demodu_IQ = [0 1 3 2 6 7 5 4]; %f(m)=(m+7)/2 + 1, so I=-7 --- 1, I=1 --- 5

idx = find(QAM_input_I7);

QAM_input_I(idx) = 7;

idx = find(QAM_input_I-7);

QAM_input_I(idx) = -7;

idx = find(QAM_input_Q7);

QAM_input_Q(idx) = 7;

idx = find(QAM_input_Q-7);

QAM_input_Q(idx) = -7;

tmp = round((QAM_input_I+7)/2) + 1;

output_frame(1:6:end) = bitget(QAM_64_Demodu_IQ(tmp),3);

output_frame(2:6:end) = bitget(QAM_64_Demodu_IQ(tmp),2);

output_frame(3:6:end) = bitget(QAM_64_Demodu_IQ(tmp),1);

tmp = round((QAM_input_Q+7)/2) + 1;

output_frame(4:6:end) = bitget(QAM_64_Demodu_IQ(tmp),3);

output_frame(5:6:end) = bitget(QAM_64_Demodu_IQ(tmp),2);

output_frame(6:6:end) = bitget(QAM_64_Demodu_IQ(tmp),1);

end

几个问题关于Matlab编写BPSK信号通过AWGN信道的仿真(在线跪求大神，不胜感激)！！！

求一份完整的Matlab编写BPSK信号通过AWGN信道仿真过程的程序。最好能有注释。在线求啊 主程序部分： %programm 3-1 %bpsk.m % % Simulation program

matlab编程实现最大似然解调 采用BPSK调制 并画出误码率曲线

您好，您这样：

clc;

clear;

fc=4800;fs=12000;fb=2400;

%要调制的数字信号

a=randint(1,12,2);%随机产生12个“0”，“1”

s=zeros(1,60);

for i=1:12

for j=1:5

if(a(i)==0)

s(j+(i-1)*5)=0;

else

s(j+(i-1)*5)=1;

end

end

end

plot(s);xlabel('基带信号');

figure

pwelch(s);%功率谱

figure

%波形成形滤波器(平方根升余弦滚降)

h=firrcos(14,1200,1200,4800,'sqrt');

figure

stem(h);xlabel('成形滤波器的单位冲击响应');

[H,W]=freqz(h,1);

H=abs(H);

figure

plot(H);xlabel('成形滤波器的频率响应');

s=fftfilt(h,s);

figure

plot(s);xlabel('通过成形滤波器后的基带信号');

figure

pwelch(s);%经波形成形滤波器后的功率谱

%已调信号

e=dmod(a,4800,2400,12000,'psk',2);%调制

figure

plot(e);xlabel('已调信号');

enoise=e+randn(1,60);%enoise=e+.1*randn(1,60)不同功率的高斯白噪声

aa=ddemod(enoise,4800,2400,12000,'psk',2);%解调

figure

stem(aa);xlabel('解调后的数字信号');%解调后的数字信号

p=symerr(a,aa)/12 %误码率

%误码率曲线

figure

r=-6:3:12;

rr=10.^(r/10);

pe1=1/2*exp(-rr);%相干解调的误码率曲线

hold on

plot(r,pe1,'r');grid on;

pe2=(1-1/2*erfc(sqrt(rr))).*erfc(sqrt(rr));%差分相干解调的误码率曲线

plot(r,pe2,'b');xlabel('bpsk,dpsk误码率曲线');

set(gca,'XTick',-6:3:18);

matlab高手请支援

应该是这句出现的问题吧，noise=randn(1,length(bpsk));这里bpsk明显没有定义啊，你是想用以g算出来的结果吧，但你前面并没有定义bpsk_output或bpsk与g的关系，因此没有bpsk这个值，程序出错，仔细检查一下看是不是少写了什么式子

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