MIMO underwater communication with sparse channel estimation

Abstract

In the area of underwater communications, MIMO (Multiple Input Multiple Output) techniques for increasing the data rates have been studied. The advantage of MIMO techniques is to increase the channel capacity, and it does not use additional frequency or transmit power. In this paper, we propose a sparse channel estimation method for MIMO underwater communication. The proposed method is comprised of the dominant channel tap position detection based on L1-norm minimization, channel regeneration, and LMS (Least Mean Square) channel estimation. To prove the performance of the proposed method, the simulations were conducted. The channels for simulation were generated by Bellhop model, and the sound speed profile that was really measured in sea was used. The range between sources and receivers is 1 km. In simulation results, the channel tracking speed of the proposed method was faster than the conventional method. The BER (Bit Error Rate) performance was improved about 10% at 15dB of SNR (Signal-to-Noise Ratio).