A model averaging approach for equalizing sparse communication channels

In communication applications it is important for equalization to have a good estimate of the channel over which the signal was transferred. In this paper we introduce the concept of model averaging, where several channel estimates are used in a weighted manner, to sparse communication channel estimation and equalization for channels with intersymbol interference. We show via numerical examples that the bit-error-rate (BER) can be reduced by our suggested method, compared to the BERs obtained using channel estimation methods not assuming any sparsity of the channel.