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Joint Maximum Likelihood Channel Estimation and Data Detection for MIMO Systems

Joint Maximum Likelihood Channel Estimation and Data Detection for MIMO Systems
Joint Maximum Likelihood Channel Estimation and Data Detection for MIMO Systems
Abstract—Blind and semiblind adaptive schemes are proposed for joint maximum likelihood (ML) channel estimation and data detection for multiple-input multiple-output (MIMO) systems. The joint ML optimisation over channel and data is decomposed into an iterative two-level optimisation loop. An efficient global optimisation search algorithm called the repeated weighted boosting search is employed at the upper level to identify the unknown MIMO channel model while an enhanced ML sphere detector called the optimised hierarchy reduced search algorithm aided ML detector is used at the lower level to perform the ML detection of the transmitted data. A simulation example is included to demonstrate the effectiveness of these two schemes.
5354-5358
Abuthinien, M.
887a123c-24d0-43ef-81d9-94091ef4b37f
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Wolfgang, A.
e87811dd-7028-4ac3-90cc-62003ff22202
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1
Abuthinien, M.
887a123c-24d0-43ef-81d9-94091ef4b37f
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Wolfgang, A.
e87811dd-7028-4ac3-90cc-62003ff22202
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1

Abuthinien, M., Chen, Sheng, Wolfgang, A. and Hanzo, L. (2007) Joint Maximum Likelihood Channel Estimation and Data Detection for MIMO Systems. IEEE ICC'07, Glasgow, UK, United Kingdom. 24 - 28 Jun 2007. pp. 5354-5358 .

Record type: Conference or Workshop Item (Paper)

Abstract

Abstract—Blind and semiblind adaptive schemes are proposed for joint maximum likelihood (ML) channel estimation and data detection for multiple-input multiple-output (MIMO) systems. The joint ML optimisation over channel and data is decomposed into an iterative two-level optimisation loop. An efficient global optimisation search algorithm called the repeated weighted boosting search is employed at the upper level to identify the unknown MIMO channel model while an enhanced ML sphere detector called the optimised hierarchy reduced search algorithm aided ML detector is used at the lower level to perform the ML detection of the transmitted data. A simulation example is included to demonstrate the effectiveness of these two schemes.

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More information

Published date: June 2007
Additional Information: Event Dates: 24-28 June 2007
Venue - Dates: IEEE ICC'07, Glasgow, UK, United Kingdom, 2007-06-24 - 2007-06-28
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 264239
URI: http://eprints.soton.ac.uk/id/eprint/264239
PURE UUID: 69d6630f-cee7-483e-b873-75b9e36d6027
ORCID for L. Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 29 Jun 2007
Last modified: 18 Mar 2024 02:34

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Contributors

Author: M. Abuthinien
Author: Sheng Chen
Author: A. Wolfgang
Author: L. Hanzo ORCID iD

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