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
May 2011
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.
VTC 2011 Spring, Budapest, Hungary.
15 - 18 May 2011.
.
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, Budapest, Hungary, 2011-05-15 - 2011-05-18
Organisations:
Southampton Wireless Group
Identifiers
Local EPrints ID: 272279
URI: http://eprints.soton.ac.uk/id/eprint/272279
PURE UUID: 02c76cd0-384a-4d53-b669-91cf6f482f33
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Date deposited: 12 May 2011 16:40
Last modified: 14 Mar 2024 09:51
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Contributors
Author:
Peichang Zhang
Author:
Indrakshi Dey
Author:
Shinya Sugiura
Author:
Sheng Chen
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