LS & MMSE channel estimators for OFDM

Compares the performance of the LS and MMSE estimators for a 64 sub-carrier OFDM model

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Here is a simulation based proof highlighting the superiority of the MMSE[Min Mean Sq Error] channel estimator over the LS[Least Sq] estimator.The two parameters of evaluation turn out to be, quite logically, the SER[Symbol Error Rate] and the Mean Square Error.The channel is assumed to be g(t)=delta(t-0.5 Ts)+delta(t-3.5 Ts)
{Fractionally spaced}.
For more information on the theory and formulae used , please do refer to the paper On "Channel Estimation In OFDM systems" By Jan-Jaap van de Beek, Ove Edfors, Magnus Sandell, Sarah Kate wilson and Petr Ola Borjesson In proceedings Of VTC'95 Vol 2 pg.815-819.The two sub folders contain the code for the simulations related to the two parameters , i.e SER and MSE..

Cite As

Vinay Prabhu (2026). LS & MMSE channel estimators for OFDM (https://www.mathworks.com/matlabcentral/fileexchange/11033-ls-mmse-channel-estimators-for-ofdm), MATLAB Central File Exchange. Retrieved .

General Information

MATLAB Release Compatibility

  • Compatible with any release

Platform Compatibility

  • Windows
  • macOS
  • Linux
Version Published Release Notes Action
1.0.0.0

As rightly pointed out by Yubing Zhang,
line 37 of the codes mse_compare and ser_compare should be:
s=s+(exp(-j*pi*(1/64)*(k+63*tau(m))) * (( sin(pi*tau(m)) / sin(pi*(1/64)*(tau(m)-k)))));
[The bracket was misplaced earlier]