# Channel Equalization for the comm.RayleighFading communication toolbox for Frequency Selective channel?

18 views (last 30 days)
Maggie Shammaa on 10 Feb 2021
Answered: Abhimenyu on 31 May 2024
I recently used the comm.rayleighfading communication toolbox to create random channel taps with some correlation (Jakes, Clarkes Models). In flat fading it is easy to obtain the H matrix and equalize accordingly. However, I dont know how it should be done using this toolbox in multipath frequency selective channels.
I want to use the channel output y and the path gains h to reconstruct the input signal x.

Abhimenyu on 31 May 2024
Hi,
I understand that you want to reconstruct the input signal (x) from the channel output (y) in a multipath frequency selective channel scenario using the path gains (h). For this, equalization techniques need to be employed. In MATLAB, you can design a equalizer based on the channel's impulse response using the comm.LinearEqualizer, comm.DecisionFeedbackEqualizer, comm.MLSEEqualizer system objects, etc.
Please follow the example MATLAB code below to understand equalization using the communication toolbox of MATLAB:
Simulate the Multipath Channel: Simulate the multipath channel using the appropriate model (e.g., Rayleigh or Rician fading). This usually involves defining the number of paths and their respective delays and average path gains.
% Example of creating a Rayleigh fading channel object
fs = 1000; % Sampling frequency in Hz
channel = comm.RayleighChannel('SampleRate',fs,'PathDelays',[0 1e-4 3e-4],'AveragePathGains',[0 -3 -6],'NormalizePathGains',true);
Pass the Signal Through the Channel: Pass your input signal (x) through the channel to obtain the channel output (y) and the path gains (h).
% Assuming x is your input signal
[y, h] = channel(x);
Equalization: To reconstruct (x) from (y), you can use various equalization techniques. For frequency selective channels, typical equalizers include Linear Equalizers (LE), Decision Feedback Equalizers (DFE), etc.
Linear Equalizers attempt to invert the channel's effect linearly.
% Example of using a linear equalizer
eq = comm.LinearEqualizer('Algorithm','LMS','NumTaps',5,'StepSize',0.01);
[x_est, err] = eq(y, x); % Assuming x is known at the receiver for training
Decision Feedback Equalizer (DFE) uses past decision outputs to cancel intersymbol interference (ISI), which is not possible in LE.
% Example of using a DFE
dfe = comm.DecisionFeedbackEqualizer('Algorithm','LMS','NumForwardTaps',5,'NumFeedbackTaps',4,'StepSize',0.01);
[x_est, err] = dfe(y, x); % Assuming x is known at the receiver for training
MLSE Equalizer equalizes modulated signals using maximum likelihood sequence estimation.
mlse = comm.MLSEEqualizer(TracebackDepth=10, Channel=chCoeffs, Constellation=pskmod(0:3,4,pi/4));
If you're using OFDM, equalization is typically performed in the frequency domain, which simplifies the process especially for channels with long impulse responses.
% Assuming Y is the received OFDM symbol in frequency domain and H is the channel frequency response
X_est = Y ./ H; % Simple division for equalization
Then the signal can be demodulated to obtain the final result.
Please follow the below-mentioned MATLAB R2024a documentation links to understand more on comm.RayleighChannel, comm.LinearEqualizer, comm.DecisionFeedbackEqualizer, comm.MLSEEqualizer system objects respectively:
Hope this helps!

### Categories

Find more on Propagation and Channel Models in Help Center and File Exchange

### Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!