Abstract

In this paper, a novel low-complexity tree-search (TS) algorithm, which is referred to as a hierarchical tree search (HTS), is proposed for soft-output multiple-input-multiple-output (MIMO) detection to mitigate the performance loss caused by an early termination. The proposed HTS algorithm is realized by the following two components: the hierarchical set partitioning to find all hypotheses with reasonable quality as fast as possible and to fairly improve them and the new cost metric to determine the search order by considering the quality of the hypotheses found so far. Through simulation, it is shown that the performance-complexity tradeoff of the proposed HTS algorithm surpasses those of the existing algorithms in various MIMO configurations.

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