PRACTICAL CONSIDERATIONS OF GREEDY COMPRESSED SAMPLING METHODS APPLICATION FOR OFDM CHANNEL ESTIMATION
A larger number of pilot carriers gives better channel state estimation but leads to lower spectrum efficiency of the system.
Objective. Primary objective of this paper is to look at the practical aspects of the application of novel CS-based channel
estimation technique, that can achieve estimation quality on reduced training data, in context of real pilot aided OFDM systems.
Method. A novel technique CS enables representation of sparse signals using fewer samples as compared to its original size.
Exploiting the sparse nature of channel impulse response of multipath channels, we apply the CS technique for channel estimation in
pilot aided OFDM system based on ISDB-T standard.
Results. In this paper, we consider two the most popular CS-based recovery algorithms – OMP and CoSaMP. The MSE
performance metrics are given for both CS-based channel estimation algorithms. Simulations results demonstrate that CoSaMP
provides more stable results while requires more pilot carriers than OMP to achieve good estimation quality. Both algorithms require
a priori knowledge of channel sparsity level but CoSaMP is much more sensitive to a correctness of this information.
Conclusions. The compressed sampling approach shows the impressive capability of channel impulse response recovery from a
significantly smaller amount of pilot carriers than traditional linear methods require. However, the need of sparsity knowledge by the
most popular CS recovery methods seriously limits the applicability of these algorithms in real OFDM receivers. Nevertheless, CSbased
channel estimation is a promising technique which worth further investigation to overcome this limitation.
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