A new optimized least-square sparse channel estimation scheme for underwater acoustic communication

In underwater acoustic (UWA) communication, orthogonal frequency division multiplexing (OFDM) is a promising technology that is highly essential to get channel state information meant for channel estimation (CE). Nevertheless, higher complexity, slower convergence, and poor performance, which degrade the performance estimation, are the limitations of the traditional CE methodologies. Thus, by amalgamating the least square (LS)-CE algorithm along with polynomial interpolated black widow optimization (PI-BWO) model, an optimized least square sparse (OLSS) CE algorithm has been proposed to intend for a UWA-OFDM communication system. Formerly, by utilizing the 2's complement shift left turbo encoding (2CSL-TE) methodology, the input signal is encoded. After that, the modulated encoded signal is provided for inverse fast Fourier transform (IFFT) operations; subsequently, they are transferred over the UWA channel toward the receiver OFDM. By employing the OLSS methodology, the received OFDM signal's interference-free region is utilized for sparse CE at the receiver. Regarding symbol error rate (SER), bit error rate (BER), mean square error (MSE), and peak signal-to-noise ratio (PSNR), the proposed model's experiential outcome is evaluated and analogized with the other prevailing methodologies. When analogized with the conventional models, the proposed estimation methodologies achieved better performance.