Soft-Input Soft-Output List Sphere Detection with a Probabilistic Radius Tightening
- Authors
- Lee, Jaeseok; Shim, Byonghyo; Kang, Insung
- Issue Date
- 8월-2012
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Sphere decoding; Iterative detection and decoding; a posteriori probability; probabilistic radius tightening; multiple-input multiple-output system; complexity reduction
- Citation
- IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, v.11, no.8, pp.2848 - 2857
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
- Volume
- 11
- Number
- 8
- Start Page
- 2848
- End Page
- 2857
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/107744
- DOI
- 10.1109/TWC.2012.060212.111311
- ISSN
- 1536-1276
- Abstract
- In this paper, we present a low-complexity list sphere detection algorithm for achieving near-optimal a posteriori probability (APP) detection in an iterative detection and decoding (IDD). Motivated by the fact that the list sphere decoding searching a fixed number of candidates is computationally inefficient in many scenarios, we design a criterion to search lattice points with non-vanishing likelihood and then derive a hypersphere radius satisfying this condition. Further, in order to exploit the original sphere constraint as it is instead of using necessary conditioned version, we combine a probabilistic tree pruning strategy and the proposed list sphere search. Two features, tightened hypersphere radius and probabilistic tree pruning, collaborate and improve the search efficiency in a complementary fashion. Through simulations on 4 x 4 MIMO system, we show that the proposed method provides substantial reduction in complexity while achieving negligible performance loss over the conventional list sphere detection.
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Collections - College of Informatics > Department of Computer Science and Engineering > 1. Journal Articles
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