Thanks col , I have checked your code , & i think i have get some idea.
I am wondering that maybe i have the same problem with Shahin. Actually i
have skipped the step in insert cyclic prefix & remove cyclic prefix in my
code , since i assume the process is ideal. Therefore there is no IBI.
Meanwhile , there is only the AWGN might affect my SER , but i really no
idea , why the theoretical SER & simulate SER is totally difference , &
the number of error is too large.
the F=ifft(eye(.....))) & direct ifft the transmitted signal actually is
the same , since i am try to do in block transmission & equalization.
And I am referring this Journal
http://www.ece.iastate.edu/~zhengdao/group/publications/papers/wagi00m.pdf
Regards
Eric
Reply by ●February 26, 20072007-02-26
On Feb 26, 9:42 am, "ericknightX" <wil...@gmail.com> wrote:
> hi all ,
>
> Recently , I have generated a OFDM signal , but meanwhile I have noticed
> that my Analytical & Computer Simulation of my SER are totally difference,
> Moreover , the Numbers of Errors in my signal also quite large, therefore i
> am wondering whether there are some Errors in my signal detection or the
> progress of generate OFDM signal. Actually I should generate channel
> estimation of OFDM signal , but i have stuck at this part quite long time
> , therefore i am really need help from all of you with my sincere.
>
> Thank you.
>
> Eric
>
hi all ,
Recently , I have generated a OFDM signal , but meanwhile I have noticed
that my Analytical & Computer Simulation of my SER are totally difference,
Moreover , the Numbers of Errors in my signal also quite large, therefore i
am wondering whether there are some Errors in my signal detection or the
progress of generate OFDM signal. Actually I should generate channel
estimation of OFDM signal , but i have stuck at this part quite long time
, therefore i am really need help from all of you with my sincere.
Thank you.
Eric
*********************************************************************************************
%generate 64 QAM signal
aqam=[-7 -5 -3 -1 1 3 5 7];
A=repmat(aqam,8,1);
B=flipud(A');
konst_qam=A+j*B;
konst_qam=konst_qam(:);
qam=konst_qam(randint(1024,1,64)+1); %Random Generate 1024 symbol of 64
QAM signal
F=ifft(eye(1024)); %Convert the signal from Frequency
domain to Time domain
Fs=F*qam;
%Fs1=repmat(Fs,1,100);
C=zeros(1024,1);
R=zeros(1,1024);
for(i=1:6)
h(1,i)=rand+j*rand;
end
R(1,1:6)=h;
C(1:6,1)=h';
H=toeplitz(C,R);
x=H*Fs;
%generate Noise
n=randn(size(x))+j*randn(size(x)); %randn generates Gaussian
distributed noise
SNR=20; %SNR-ratio
p=std(x)/(std(n)*10^(SNR/20));
%add noise to signal
x1=x+n*p;
%Receiver
F1=fft(eye(1024)); %Convert the Signal back from Time Domain to Frequency
Domain.
y1=F1*x1;
D=F1*H*F;
%Equalization
s_final1=(inv(D))*y1;
%Symbol Detection
s_f1=repmat(s_final1,1,64).';
konst_block=repmat(konst_qam,1,1024);
distance1=abs(s_f1-konst_block);
[z1,ind_2]=min(distance1);
qam_det1=konst_qam(ind_2);
%Theoretical SER
d=2;
sigma=std(real(n*p));
Q=0.5*erfc(d/(sqrt(2)*2*sigma));
sep_theo1=3.5*Q-3.0625*Q^2;
%Simulated SER
error=sum(qam~=qam_det1);
sep=error/1024;