Radius-adaptive sphere decoding via probabilistic tree pruning

Byonghyo Shim, Insung Kang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

In this paper, we propose a radius-adaptive sphere decoding algorithm that reduces the number of operations in sphere-constrained search while achieving performance close to ML decoding. Specifically, by adding a probabilistic noise constraint on top of sphere constraint, a more stringent necessary condition is provided, particularly at an early stage, and hence many branches that are unlikely to be selected are removed in the early stage of sphere search. From the simulation in a frequency selective channels with pruning probability ε = 0.03, it is shown that the computational complexity of proposed strategy reduces significantly (30-76%) over the original algorithm with negligible performance loss.

Original languageEnglish
Title of host publicationIEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
Publication statusPublished - 2007 Dec 1
Externally publishedYes
Event8th IEEE Signal Processing Advances in Wireless Communications, SPAWC 2007 - Helsinki, Finland
Duration: 2007 Jun 172007 Jun 20

Other

Other8th IEEE Signal Processing Advances in Wireless Communications, SPAWC 2007
CountryFinland
CityHelsinki
Period07/6/1707/6/20

ASJC Scopus subject areas

  • Signal Processing
  • Engineering(all)

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  • Cite this

    Shim, B., & Kang, I. (2007). Radius-adaptive sphere decoding via probabilistic tree pruning. In IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC [4401321]