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Semi-blind joint maximum likelihood channel estimation and data detection for MIMO systems

Abuthinien, M., Chen, S. and Hanzo, L. (2008) Semi-blind joint maximum likelihood channel estimation and data detection for MIMO systems IEEE Signal Processing Letters, 15, pp. 202-205.

Record type: Article

Abstract

Semi-blind joint maximum likelihood (ML) channel estimation and data detection is proposed for multiple-input multiple-output (MIMO) systems. The joint ML optimization over channel and data is decomposed into an iterative two-level optimization loop. An efficient optimization search algorithm referred to as the repeated weighted boosting search (RWBS) is employed at the upper level to identify the unknown MIMO channel while an enhanced ML sphere detector termed as the optimized hierarchy reduced search algorithm is used at the lower level to perform ML detection of the transmitted data. Only a minimum pilot overhead is required to aid the RWBS channel estimator’s initial operation, which not only speeds up convergence but also avoids ambiguities inherent in blind joint estimation of both the channel and data. Index Terms—Channel estimation, data detection, joint maximum likelihood estimation, multiple-input multiple-output.

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Published date: 2008
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 265097
URI: http://eprints.soton.ac.uk/id/eprint/265097
PURE UUID: ae830550-426e-44aa-9dd1-34e40b247b68

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Date deposited: 23 Jan 2008 09:42
Last modified: 18 Jul 2017 07:29

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Contributors

Author: M. Abuthinien
Author: S. Chen
Author: L. Hanzo

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