MMLSE is known to be the most suitable approach for space-time (S-T) receivers that requires the knowledge of the S-T channel response. In general we do not have the knowledge neither of the channel H nor of co-channel interference's (CCI) statistics, these have to be estimated by using training sequences. When short data preambles are available the large variance of the unconstrained estimate of the multichannel H can heavily affect the achievable performance. This paper illustrates the advantages of a low rank truncation of the whitened channel in a mobile radio scenario where the S-T diversity of the channel is almost limited. The benefits achievable with this class of low-rank receivers are the reduction the variance of the multichannel response estimate and the lower complexity compared to a full-rank solution. The performances in realistic scenarios demonstrate the advantages compared to conventional receivers.

Variable rank receiver structures for low-rank space-time channels

Spagnolini, U.
1999-01-01

Abstract

MMLSE is known to be the most suitable approach for space-time (S-T) receivers that requires the knowledge of the S-T channel response. In general we do not have the knowledge neither of the channel H nor of co-channel interference's (CCI) statistics, these have to be estimated by using training sequences. When short data preambles are available the large variance of the unconstrained estimate of the multichannel H can heavily affect the achievable performance. This paper illustrates the advantages of a low rank truncation of the whitened channel in a mobile radio scenario where the S-T diversity of the channel is almost limited. The benefits achievable with this class of low-rank receivers are the reduction the variance of the multichannel response estimate and the lower complexity compared to a full-rank solution. The performances in realistic scenarios demonstrate the advantages compared to conventional receivers.
1999
IEEE VTS 50th Vehicular Technology Conference, VTC 1999-Fall
0780354354
Computer Science Applications1707 Computer Vision and Pattern Recognition; Electrical and Electronic Engineering; Applied Mathematics
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1047719
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