Apriori-LLR-Threshold-Assisted K-Best Sphere Detection for MIMO Channels

Wang, Li, Xu, Lei, Chen, Sheng and Hanzo, Lajos (2008) Apriori-LLR-Threshold-Assisted K-Best Sphere Detection for MIMO Channels. In, IEEE VTC'08 (Spring), Marina Bay, Singapore, 11 - 14 May 2008. , 867-871.


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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.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Event Dates: 11-14 May 2008
Divisions: Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Comms, Signal Processing & Control
ePrint ID: 265904
Date Deposited: 11 Jun 2008 13:51
Last Modified: 27 Mar 2014 20:10
Further Information:Google Scholar
ISI Citation Count:0
URI: http://eprints.soton.ac.uk/id/eprint/265904

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