A New Adaptive OMP-MAP Algorithm-Based Iterative Sparse Channel Estimation for OFDM Underwater Communication

A sparse channel estimation approach based on doubly spread underwater acoustic (UWA) channels is widely used to detect coherent acoustic orthogonal frequency division multiplexing (OFDM) signals. A new time-domain channel estimation (CE) technique for OFDM based UWA communication with Rician fading is used to exploit the channel sparsity. First, to improve the estimation accuracy in high noise conditions, we have exploited the channel sparsity to generate a closed-form equation for the termination condition. Then, in low-level noise instances, the additional criterion to balance estimation accuracy and computing costs has been established. By incorporating these two requirements within the orthogonal-matching-pursuit (OMP) structure, an adaptive-OMP (AOMP) algorithm has been proposed. The AOMP and maximum a posteriori probability (MAP) techniques are combined to provide a computationally efficient, and a new AOMP-MAP scheme for estimating the sparse complex channel path gain has been proposed. Further, The minimum variance unbiased estimator is used to improve the proposed CE technique. Exploiting the experimental channel data, computer simulations reveal that the proposed CE technique obtains the outstanding outcomes.