Exploiting Spatial–Temporal Joint Sparsity for Underwater Acoustic Multiple-Input–Multiple-Output Communications

Multiple-input–multiple-output (MIMO) system offers a promising way for high data rate communication over bandwidth-limited underwater acoustic channels. However, MIMO not only suffers from intersymbol interference, but also introduces the additional co-channel which brings challenge channel estimation and equalization. In this article, we propose novel interference cancellation (IC) methods handling problem in design of both Our method utilizes spatial joint sparsity temporal multipath structure to estimate sparse channels with common delays under distributed compressed sensing framework. way, enhance estimates delays, thus, suppress interference. Meanwhile, address case arrivals different are estimated as noise simultaneous orthogonal matching pursuit (SOMP) algorithm, introduce forward–reverse strategy SOMP is referred FRSOMP algorithm. proposed algorithm performs achieve initial estimates, forward-add process, attempts add candidates into support sets, reverse-fetch process check if set retained or removed. The purpose directly calculate filter coefficients channel-estimation-based decision feedback equalization (CE-DFE). CE-DFE receiver IC component. We filters based on traditional CE-DFE, derive feedforward filters, metric obtained by so will be suppressed demonstrate performance our approach numerical simulation, lake experiment, sea experiment. Results provided effectiveness methods, show that obtain higher output signal-to-noise ratio, lower bit error rate, more separated constellations compared method.