Adaptive channel equalization using NLMS & Variable step size NLMS algorithms using Simulink

Compare the performance of NLMS and variable step size NLMS algorithms in adaptive channel equalization using Simulink. Two equalizer are used linear and non-linear for comarison. The channels are AWGN and Multipath fading channels. The required outputs are four curves:

1- MSE vs Iteration number

2- BER vs SNR

3- Number of taps vs MSE

4- Number of taps vs BER

The main goal of this project is to appreciate the variable step size NLMS algorithm over standard NLMS algortihm since it solves the problem of trading off between the rate of convegence and stability caused by changing the step size.

I have a paper for a variable step size NLMS that has the algortihm I wanted to be implemented

## Deliverables

1) Complete and fully-functional working program(s) in executable form as well as complete source code of all work done.

2) Deliverables must be in ready-to-run condition, as follows (depending on the nature of the deliverables):

a) For web sites or other server-side deliverables intended to only ever exist in one place in the Buyer's environment--Deliverables must be installed by the Seller in ready-to-run condition in the Buyer's environment.

b) For all others including desktop software or software the buyer intends to distribute: A software installation package that will install the software in ready-to-run condition on the platform(s) specified in this bid request.

3) All deliverables will be considered "work made for hire" under U.S. Copyright law. Buyer will receive exclusive and complete copyrights to all work purchased. (No GPL, GNU, 3rd party components, etc. unless all copyright ramifications are explained AND AGREED TO by the buyer on the site per the coder's Seller Legal Agreement).

## Platform


Habilidades: Varios, Mathlab y Mathematica

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Información del empleador:
( 0 comentarios ) United Kingdom

Nº del proyecto: #3740394

1 freelancer está ofertando el promedio de $68 para este trabajo


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$68 USD en 15 días
(17 comentarios)