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Semi-blind adaptive space-time shift keying systems based on iterative channel estimation and data detection

Semi-blind adaptive space-time shift keying systems based on iterative channel estimation and data detection
Semi-blind adaptive space-time shift keying systems based on iterative channel estimation and data detection
We develop a semi-blind adaptive space-time shift keying (STSK) based multiple-input multiple-output system using a low-complexity iterative channel estimation and data detection scheme. We first employ the minimum number of STSK training blocks, which is related to the number of transmitter antennas, to obtain a rough least square channel estimate (LSCE). Low-complexity single-stream maximum likelihood (ML) data detection is then carried out based on the initial LSCE and the detected data are utilised to refine the decision-directed LSCE. We show that a few iterations are sufficient to approach the optimal ML detection performance obtained with the aid of perfect channel state information.
5 pages
Zhang, Peichang
e87b4adb-ec8a-47e9-a73e-5b9140f5dc9d
Dey, Indrakshi
c155baa9-5bdb-4be1-9f92-e36050f4ea20
Sugiura, Shinya
4c8665dd-1ad8-4dc0-9298-bf04eded3579
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Zhang, Peichang
e87b4adb-ec8a-47e9-a73e-5b9140f5dc9d
Dey, Indrakshi
c155baa9-5bdb-4be1-9f92-e36050f4ea20
Sugiura, Shinya
4c8665dd-1ad8-4dc0-9298-bf04eded3579
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80

Zhang, Peichang, Dey, Indrakshi, Sugiura, Shinya and Chen, Sheng (2011) Semi-blind adaptive space-time shift keying systems based on iterative channel estimation and data detection. At VTC 2011 Spring VTC 2011 Spring, Hungary. 15 - 18 May 2011. 5 pages.

Record type: Conference or Workshop Item (Other)

Abstract

We develop a semi-blind adaptive space-time shift keying (STSK) based multiple-input multiple-output system using a low-complexity iterative channel estimation and data detection scheme. We first employ the minimum number of STSK training blocks, which is related to the number of transmitter antennas, to obtain a rough least square channel estimate (LSCE). Low-complexity single-stream maximum likelihood (ML) data detection is then carried out based on the initial LSCE and the detected data are utilised to refine the decision-directed LSCE. We show that a few iterations are sufficient to approach the optimal ML detection performance obtained with the aid of perfect channel state information.

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More information

Published date: May 2011
Additional Information: Event Dates: May 15-18, 2011
Venue - Dates: VTC 2011 Spring, Hungary, 2011-05-15 - 2011-05-18
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 272279
URI: https://eprints.soton.ac.uk/id/eprint/272279
PURE UUID: 02c76cd0-384a-4d53-b669-91cf6f482f33

Catalogue record

Date deposited: 12 May 2011 16:40
Last modified: 18 Jul 2017 06:32

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Contributors

Author: Peichang Zhang
Author: Indrakshi Dey
Author: Shinya Sugiura
Author: Sheng Chen

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