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sign sign lms
if your knowledge about LMS is good enough then sign-sign has just some minor modification for reducing complexity.
for LMS haykin's "adaptive filtering theory" book is a good reference. however if you are looking for advanced mathematical stuff in adaptive filtering then without...
awgn channel
The first error is that you are using the same variance for H as the noise. so that your received sequence will be a total noise and it is obvious that the BER is 1/2. you should normalize H matrix to have variance equal to one so that it won't affect the SNR...
I don't see were you are facing problem?
simply generate your MPSK signal using randsrc then use ifft(.) for this signal to generate OFDM signal and then add CP to the begining of OFDM signal
Diversity order
for deriving the diversity order in an analytical way you should have your BER formula. when SNR tends to infinity the slope of BER vs. SNR in logscale shows the diversity order.
for example -20dB/dec slope shows one diversity order. -30dB/dec shows 1.5 diversity order: this...
MRC
I assume you are talking about demodulation of the transmitted signal.
\alpha_k is define in a way to maximize the received SNR in the receiver hence the name MRC. for Gaussian noise, it can be shown that \alpha_k is equal to conj(h_j).
Also note that the receiver does not combine the...
Re: Any good material on Eqalizer?
Hi naveed,
you can find a brief discussion about equalizers on Rappaport "wireless communications" book on
chapter 7 or 9 if I recall.
For advanced topic you may refer to:
"adaptive filter theory" by Haykin which cover mostly the adaptive equalizers
or...
Rr >Tr ....MIMO
the answer is that we always assume that we can achieve channel parameter at the receiver so we can exploit receive diversity and the more the number of Rx antennas the better diversity we have at the receiver but in the transmitter we dont have channel estimation unless we...
what is awgn channel
when we say that a process is white we just define its second moment,but by knowing that its gaussian some more information will be known such as mean,etc.
and about randn. it produce a white gaussian noise because its samples are uncorrelated and so its white,to produce a...
Re: Proakis
to understand proakis u should first read the book by proakis & salehi and then the former one.this combination is great.but if u just want to read some specific chapters i can suggest better books for them.
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