List sphere decoding with a probabilistic radius tightening

Jaeseok Lee, Byonghyo Shim, Insung Kang

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

1 Citation (Scopus)

Abstract

In this paper, we present a low-complexity list sphere search algorithm for achieving near-optimal a posteriori probability (APP) detection in iterative detection and decoding (IDD). Motivated by the fact that the list sphere decoding searching a fixed number of lattice points is inefficient in many scenarios, we design a criterion to search lattice points with non-vanishing likelihood and derive the optimal sphere radius satisfying this requirement. Further, in order to exploit the sphere constraint as it is instead of using necessary conditioned versions, we incorporate a probabilistic tree pruning strategy into the list sphere search. Through simulations on realistic IDD systems, we show that the proposed method provides considerable complexity savings while maintaining near-optimal performance.

Original languageEnglish
Title of host publication2010 IEEE Global Telecommunications Conference, GLOBECOM 2010
DOIs
Publication statusPublished - 2010
Event53rd IEEE Global Communications Conference, GLOBECOM 2010 - Miami, FL, United States
Duration: 2010 Dec 62010 Dec 10

Publication series

NameGLOBECOM - IEEE Global Telecommunications Conference

Other

Other53rd IEEE Global Communications Conference, GLOBECOM 2010
CountryUnited States
CityMiami, FL
Period10/12/610/12/10

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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  • Cite this

    Lee, J., Shim, B., & Kang, I. (2010). List sphere decoding with a probabilistic radius tightening. In 2010 IEEE Global Telecommunications Conference, GLOBECOM 2010 [5684113] (GLOBECOM - IEEE Global Telecommunications Conference). https://doi.org/10.1109/GLOCOM.2010.5684113