Compressed channel feedback for correlated massive MIMO systems

Author

Yeon-Geun Lim ; Chan-Byoung Chae

Author_Institution

Sch. of Integrated Technol., Yonsei Univ., Seoul, South Korea

fYear

2014

fDate

10-14 June 2014

Firstpage

360

Lastpage

364

Abstract

In this paper, we propose compressive sensing-based channel quantization feedback that is appropriate for practical massive multiple-input multiple-output (MIMO) systems. We assume that the base station (BS) has a compact (2-dimensional) uniform square array that has a highly correlated channel. To serve multiple users, the BS uses a zero-forcing precoder. Our proposed channel feedback algorithm can reduce feedback overhead as well as a codebook search complexity. Numerical simulations confirm our analytical results.

Keywords

MIMO communication; channel coding; compressed sensing; correlation methods; feedback; numerical analysis; precoding; quantisation (signal); wireless channels; 2-dimensional uniform square array; BS; base station; channel quantization feedback; codebook search complexity; compressed channel feedback; compressive sensing; correlated massive MIMO system; feedback overhead reduction; multiple-input multiple-output system; numerical simulation; zero-forcing precoder; Array signal processing; Arrays; Channel estimation; Complexity theory; MIMO; Sparse matrices; Vectors; Massive MIMO; codebook; compressive sensing; ergodic achievable rate; limited feedback;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications Workshops (ICC), 2014 IEEE International Conference on

Conference_Location

Sydney, NSW

Type

conf

DOI

10.1109/ICCW.2014.6881223

Filename

6881223