Performance analysis of an mimo channel esimator based on superimposed training and first-order statistics

Author

Tugnait, Jitendra K. ; Shuangchi He

Author_Institution

Dept. of Electr. & Comput. Eng., Auburn Univ., AL

fYear

2005

fDate

17-20 July 2005

Firstpage

1336

Lastpage

1341

Abstract

Channel estimation for multiple-input multiple-output (MIMO) time-invariant channels using superimposed training is considered. Recently in X. Meng and J.K. Tugnait (2004), the first-order statistics-based approach of J.K. Tugnait and Weilin Luo (2003) was extended to multiuser systems (where semiblind versions using linear MMSE equalizers or Viterbi detectors were also presented). In this paper we present a performance analysis of the approach of X. Meng and J.K. Tugnait (2004) to obtain a closed-form expression for the channel estimation variance. We then address the issue of superimposed training power allocation for complex Gaussian random (Rayleigh) channels for MIMO systems arising from spatial multiplexing of a single user signal. Illustrative simulation examples are provided

Keywords

Gaussian channels; MIMO systems; Rayleigh channels; channel estimation; multiplexing; statistical analysis; MIMO channel estimator; Rayleigh channels; complex Gaussian random channels; first-order statistics; multiple-input multiple-output; spatial multiplexing; superimposed training power allocation; time-invariant channels; Channel estimation; Detectors; Equalizers; Information rates; MIMO; Performance analysis; Receiving antennas; Statistical analysis; Statistics; Viterbi algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Statistical Signal Processing, 2005 IEEE/SP 13th Workshop on

Conference_Location

Novosibirsk

Print_ISBN

0-7803-9403-8

Type

conf

DOI

10.1109/SSP.2005.1628803

Filename

1628803