Direct adaptive equalization based on fast sparse recursive least squares algorithms for multiple-input multiple-output underwater acoustic communications

Zhen Qin; Jun Tao; Xiaoyan Wang; Xinwei Luo; Xiao Han

doi:10.1121/1.5096630

Direct adaptive equalization based on fast sparse recursive least squares algorithms for multiple-input multiple-output underwater acoustic communications

J Acoust Soc Am. 2019 Apr;145(4):EL277. doi: 10.1121/1.5096630.

Authors

Zhen Qin¹, Jun Tao¹, Xiaoyan Wang¹, Xinwei Luo¹, Xiao Han²

Affiliations

¹ Key Laboratory of Underwater Acoustic Signal Processing of the Ministry of Education, School of Information Science and Engineering, Southeast University, Nanjing, 210096, China.
² Acoustic Science and Technology Laboratory, Harbin Engineering University, Harbin, 150001, Chinazqin@seu.edu.cn, jtao@seu.edu.cn, xyan@seu.edu.cn, luoxinwei@seu.edu.cn, hanxiao1322@hrbeu.edu.cn.

PMID: 31046369
DOI: 10.1121/1.5096630

Abstract

The sparse direct adaptive equalizer (DAE) has recently attracted much attention in underwater acoustic (UWA) communications for its improved performance compared with conventional non-sparse DAEs. The recursive least squares (RLS) type sparse DAEs were barely studied, mainly due to their high complexity despite fast convergence. This letter presents several low-complexity sparse RLS algorithms for multiple-input multiple-output UWA channel equalization. The resulting fast sparse RLS DAEs are tested to be effective and outperform their non-sparse counterpart by experimental results.