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hi all ,

Currently , i need to generate an Blind channel estimation in my OFDM
system , but i am really not that understand about the blind channel
estimation , for my understanding , i only know that we can use the
training sequence from transmitted signal to estimate the channel.Ya ,
this is very very brief understanding.

but frankly to say , i cant found any useful reference or source about
blind channel estimation . 

Meanwhile i also not that understand what is the usage of one-tap
equalizer , as i know it's use to get the MMSE estimation , but what's it
actually for , & why i will need RLS, ARMA model. No doubt i am really get
confuse on it. 

Therefore i really hope that someone can give me a short brief about it or
a simple matlab code , because i have generate my OFDM signal already , but
i am no idea about the algorithm of blind channel estimation & others.

Best Regards

Eric

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hi eric,
          many a researchers dealt with using some kind of
precoding..in blind channel estimatin..however..one simple solution
could be using higher order statistics or using nulls (or both
combinedly) in the ofdm symbol

also you can go for MMSE based one..

below i will just run through the way.

C1, C2,C3,C4---> constellation points of qpsk

your ofdm symbol will be something like..

symbol_before_IFFT = [C1 C3 C4 0 0 C2 C3 C4 C1] ;
symbol_after_IFFT = ifft([C1 C3 C4 0 0 C2 C3 C4 C1] );         denoted
by X


R(t) = H(t)*X(t) + N(t);

M(t) = FFT(R(t));

take M(t).^4 so any QPSK constellation should converged to 1 ideally
if no noise or no impairment has been added.
in presence of impairments it is not.so

if no impairments (after M(t)^4 )

symbol after FFT = [1 1 1 0 0 1 1 1 1];

if impairments are there..( after M(t)^4 )

symbol after FFT = [C1_cap  C3_cap  C4_cap   0_cap 0_cap  C2_cap
C3_cap  C4_cap  C1_cap];

so now..you can easily..pick from here taking the thing as..if
impairments were not there its [1 1 1 0 0 1 1 1 1];
if impairments are there its  [C1_cap  C3_cap  C4_cap   0_cap 0_cap
C2_cap  C3_cap  C4_cap  C1_cap];

so now from here you can pick up..
remember..this can work for a constant modulation over all.subcarriers
in OFDM symbol.

regards
particle filter reddy




take FFT(R(t)) and then square each






On Mar 2, 10:27 am, "ericknightX" <wil...@gmail.com> wrote:
> hi all ,
>
> Currently , i need to generate an Blind channel estimation in my OFDM
> system , but i am really not that understand about the blind channel
> estimation , for my understanding , i only know that we can use the
> training sequence from transmitted signal to estimate the channel.Ya ,
> this is very very brief understanding.
>
> but frankly to say , i cant found any useful reference or source about
> blind channel estimation .
>
> Meanwhile i also not that understand what is the usage of one-tap
> equalizer , as i know it's use to get the MMSE estimation , but what's it
> actually for , & why i will need RLS, ARMA model. No doubt i am really get
> confuse on it.
>
> Therefore i really hope that someone can give me a short brief about it or
> a simple matlab code , because i have generate my OFDM signal already , but
> i am no idea about the algorithm of blind channel estimation & others.
>
> Best Regards
>
> Eric

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Thanks, PARTICLEREDDY. 
Since my tutor has advised me to use a one tap equalizer to get the
optimal MMSE estimation. Can you briefly explain it to me.

The coefficient of one tap equalizer :

Wi= (Ri ^ 0.5 * Hi )/(Ri* llHill ^2+ sigma^2)

Ri=E[ ll Xi,k ll^2].             where Xi,k is the transmitted signal.

I am really not understand about the Ri as E stand for what in maths.

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On Mar 2, 9:38 am, "ericknightX" <wil...@gmail.com> wrote:
> Thanks, PARTICLEREDDY.
> Since my tutor has advised me to use a one tap equalizer to get the
> optimal MMSE estimation. Can you briefly explain it to me.
>
> The coefficient of one tap equalizer :
>
> Wi= (Ri ^ 0.5 * Hi )/(Ri* llHill ^2+ sigma^2)
>
> Ri=E[ ll Xi,k ll^2].             where Xi,k is the transmitted signal.
>
> I am really not understand about the Ri as E stand for what in maths.


The symbol E probably (ha) means expectation, or average.

||.||^2 means squared norm.

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