Detection for MIMO systems with imprecise channel knowledge

Author

Wu, Yunnan ; Kung, S.E.

Author_Institution

Dept. of Electr. Eng., Princeton Univ., NJ, USA

Volume

4

fYear

2003

fDate

6-10 April 2003

Abstract

We investigate signal detection for MIMO systems with imprecise channel knowledge. The optimal detector is one which best matches the "total" observation matrix and a "total" signal matrix which has a finite alphabet constraint and a Sylvester structure constraint. An iterative local optimization with interference cancellation (LOIC) algorithm is proposed to achieve low complexity and exploit the finite alphabet constraint. Simulation results show that our proposed algorithms can detect signals with BER close to the case of perfect channel knowledge, if a rough channel estimate is available initially.

Keywords

MIMO systems; channel estimation; computational complexity; error statistics; interference suppression; iterative methods; matrix algebra; optimisation; signal detection; time-varying channels; BER; MIMO systems; Sylvester structure constraint; channel estimation; finite alphabet constraint; imprecise channel knowledge; interference cancellation; iterative local optimization; perfect channel knowledge; signal detection; time-varying channels; total observation matrix; total signal matrix; Coherence; Constraint optimization; Detectors; Estimation; Interference cancellation; Interference constraints; Iterative algorithms; MIMO; Signal detection; Transmitting antennas;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on

ISSN

1520-6149

Print_ISBN

0-7803-7663-3

Type

conf

DOI

10.1109/ICASSP.2003.1202527

Filename

1202527