期刊论文详细信息
Applied Sciences
Early Neighbor Rejection-Aided Tabu Search Detection for Large MIMO Systems
Jin-Sil Park1  Gwang-Jae Jang1  Ju-Dong Lee1  Uzokboy Ummatov1 
[1] Research and Development, TJ-INNOVATION, Jomaru-ro 385, Beon-gil, Bucheon-si 14557, Gyeonggi-do, Korea;
关键词: multiple-input multiple-output (MIMO);    tabu search (TS);    neighbor examination;   
DOI  :  10.3390/app11167305
来源: DOAJ
【 摘 要 】

In this study, a low complexity tabu search (TS) algorithm for multiple-input multiple-output (MIMO) systems is proposed. To reduce the computational complexity of the TS algorithm, early neighbor rejection (ENR) and layer ordering schemes are employed. In the proposed ENR-aided TS (ENR-TS) algorithm, the least promising k neighbors are excluded from the neighbor set in each layer, which reduces the computational complexity of neighbor examination in each TS iteration. For efficient computation of the neighbors’ metrics, the ENR scheme can be incorporated into QR decomposition-aided TS (ENR-QR-TS). To further reduce the complexity and improve the performance of the ENR-QR-TS scheme, a layer ordering scheme is employed. The layer ordering scheme determines the order in which layers are detected based on their expected metrics, which reduces the risk of excluding likely neighbors in early layers. The simulation results show that the ENR-TS achieves nearly the same performance as the conventional TS while providing up to 82% complexity reduction.

【 授权许可】

Unknown   

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