Low-complexity adaptive tree search algorithm for MIMO detection

Kuei Chiang Lai; Li Wei Lin

doi:10.1109/TWC.2009.080902

Low-complexity adaptive tree search algorithm for MIMO detection

Kuei Chiang Lai
, Li Wei Lin

Institute of Computer and Communication Engineering

Research output: Contribution to journal › Article › peer-review

30 Citations (Scopus)

Abstract

In this paper, a reduced-complexity multiple-input multiple-output (MIMO) detector for the spatial multiplexing systems is described. It incorporates the idea of Ungerboeck's set partitioning in the tree search to reduce the computational complexity. An algorithm that adapts the number of partitions based on the channel conditions is proposed to achieve a better tradeoff between complexity and performance. Simulation results are presented to demonstrate the efficacy of the proposed algorithm under the assumptions of perfect channel and noise power estimates.

Original language	English
Pages (from-to)	3716-3726
Number of pages	11
Journal	IEEE Transactions on Wireless Communications
Volume	8
Issue number	7
DOIs	https://doi.org/10.1109/TWC.2009.080902
Publication status	Published - 2009 Jul

All Science Journal Classification (ASJC) codes

Computer Science Applications
Electrical and Electronic Engineering
Applied Mathematics

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10.1109/TWC.2009.080902

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AB - In this paper, a reduced-complexity multiple-input multiple-output (MIMO) detector for the spatial multiplexing systems is described. It incorporates the idea of Ungerboeck's set partitioning in the tree search to reduce the computational complexity. An algorithm that adapts the number of partitions based on the channel conditions is proposed to achieve a better tradeoff between complexity and performance. Simulation results are presented to demonstrate the efficacy of the proposed algorithm under the assumptions of perfect channel and noise power estimates.

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Low-complexity adaptive tree search algorithm for MIMO detection

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