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Semi-blind joint channel estimation and data detection for space-time shift keying systems

Semi-blind joint channel estimation and data detection for space-time shift keying systems
Semi-blind joint channel estimation and data detection for space-time shift keying systems
A low-complexity semi-blind joint channel estimation and data detection scheme is proposed for space-time shift keying (STSK) based multiple-input multiple-output systems. The minimum number of STSK training blocks, which is related to the number of transmitter antennas, is first utilized to provide a rough initial least square channel estimate (LSCE). Then low-complexity single-stream maximum likelihood (ML) data detection is carried out based on the initial LSCE and the detected data are employed to refine the decision directed LSCE. It is demonstrated that a few iterations are sufficient to approach the optimal ML detection performance obtained with the perfect channel state information.
993-996
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Sugiura, Shinya
4c8665dd-1ad8-4dc0-9298-bf04eded3579
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Sugiura, Shinya
4c8665dd-1ad8-4dc0-9298-bf04eded3579
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Chen, Sheng, Sugiura, Shinya and Hanzo, Lajos (2010) Semi-blind joint channel estimation and data detection for space-time shift keying systems. IEEE Signal Processing Letters, 17 (12), 993-996.

Record type: Article

Abstract

A low-complexity semi-blind joint channel estimation and data detection scheme is proposed for space-time shift keying (STSK) based multiple-input multiple-output systems. The minimum number of STSK training blocks, which is related to the number of transmitter antennas, is first utilized to provide a rough initial least square channel estimate (LSCE). Then low-complexity single-stream maximum likelihood (ML) data detection is carried out based on the initial LSCE and the detected data are employed to refine the decision directed LSCE. It is demonstrated that a few iterations are sufficient to approach the optimal ML detection performance obtained with the perfect channel state information.

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Published date: December 2010
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 271665
URI: http://eprints.soton.ac.uk/id/eprint/271665
PURE UUID: 60013b75-8034-4e67-b404-dee405479007
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

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Date deposited: 31 Oct 2010 09:51
Last modified: 18 Mar 2024 02:34

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Contributors

Author: Sheng Chen
Author: Shinya Sugiura
Author: Lajos Hanzo ORCID iD

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