Apriori-LLR-Threshold-Assisted K-Best Sphere Detection for MIMO Channels
Apriori-LLR-Threshold-Assisted K-Best Sphere Detection for MIMO Channels
When the maximum number of best candidates retained at each tree search level of the K-Best Sphere Detection (SD) is kept low for the sake of maintaining a low memory requirement and computational complexity, the SD may result in a considerable performance degradation in comparison to the full-search based Maximum Likelihood (ML) detector. In order to circumvent this problem, in this contribution we propose a novel complexity-reduction scheme, referred to as the Apriori-LLRThreshold (ALT) based technique for the K-best SD, which was based on the exploitation of the a priori LLRs provided by the outer channel decoder in the context of iterative detection aided channel coded systems. For example, given a BER of 10?5, a near-ML performance is achieved in an (8×4)-element rank-deficient 4-QAM system, despite imposing a factor two reduced detection candidate list generation related complexity and a factor eight reduced extrinsic LLR calculation related complexity, when compared to the conventional SD-aided iterative benchmark receiver. The associated memory requirements were also reduced by a factor of eight.
867-871
Wang, Li
f54669eb-8e6b-43ea-a6df-47cda21d6950
Xu, Lei
ec8d4856-7b30-4dc5-8a8b-05157450e274
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
March 2008
Wang, Li
f54669eb-8e6b-43ea-a6df-47cda21d6950
Xu, Lei
ec8d4856-7b30-4dc5-8a8b-05157450e274
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Wang, Li, Xu, Lei, Chen, Sheng and Hanzo, Lajos
(2008)
Apriori-LLR-Threshold-Assisted K-Best Sphere Detection for MIMO Channels.
IEEE VTC'08 (Spring), Marina Bay, Singapore.
11 - 14 May 2008.
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
When the maximum number of best candidates retained at each tree search level of the K-Best Sphere Detection (SD) is kept low for the sake of maintaining a low memory requirement and computational complexity, the SD may result in a considerable performance degradation in comparison to the full-search based Maximum Likelihood (ML) detector. In order to circumvent this problem, in this contribution we propose a novel complexity-reduction scheme, referred to as the Apriori-LLRThreshold (ALT) based technique for the K-best SD, which was based on the exploitation of the a priori LLRs provided by the outer channel decoder in the context of iterative detection aided channel coded systems. For example, given a BER of 10?5, a near-ML performance is achieved in an (8×4)-element rank-deficient 4-QAM system, despite imposing a factor two reduced detection candidate list generation related complexity and a factor eight reduced extrinsic LLR calculation related complexity, when compared to the conventional SD-aided iterative benchmark receiver. The associated memory requirements were also reduced by a factor of eight.
Text
lw-lx-sqc-lh-VTC08spring.pdf
- Other
More information
Published date: March 2008
Additional Information:
Event Dates: 11-14 May 2008
Venue - Dates:
IEEE VTC'08 (Spring), Marina Bay, Singapore, 2008-05-11 - 2008-05-14
Organisations:
Southampton Wireless Group
Identifiers
Local EPrints ID: 265904
URI: http://eprints.soton.ac.uk/id/eprint/265904
PURE UUID: 2e6fb03c-ad36-4fa4-abe1-cb84b633f605
Catalogue record
Date deposited: 11 Jun 2008 13:51
Last modified: 18 Mar 2024 02:34
Export record
Contributors
Author:
Li Wang
Author:
Lei Xu
Author:
Sheng Chen
Author:
Lajos Hanzo
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics