The K-Best algorithm for MIMO detections has been widely used in wireless communication systems. In this paper, to increase the throughput cost-effectively, two novel computational schemes are applied to design the K-Best detector. To reduce the number of visiting leaf nodes, we propose the pre-screening based enumeration, and almost half of leaf nodes are reduced for fast searches. To reduce the complexity of the sorting scheme, we apply the simplified Batcher's odd-even sorting algorithm (SBOESA) without sorting all outputs, and the required comparators are reduced through the simplified fast sorting design. The proposed 4×4 MIMO K-Best detector at 64QAM is implemented by TSMC 90nm process. The throughput of the proposed MIMO detector achieves up to 4.4Gbps. Compared with other designs, the proposed K-Best detector provides larger throughputs and performs superior hardware efficiency.
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机译：用于MIMO检测的K-BEST算法已广泛用于无线通信系统。在本文中，为了提高吞吐量成本，应用了两种新颖的计算方案来设计K-Best探测器。为了减少访问叶节点的数量，我们提出了基于预筛选的枚举，并且对于快速搜索，几乎一半的叶节点减少。为了降低排序方案的复杂性，我们应用简化的Batcher的奇数分类算法（SBoesa）而不对所有输出进行排序，并且所需的比较器通过简化的快速分拣设计减少。在64QAM时提出的4×4 MIMO K-BEST探测器由TSMC 90nm过程实现。所提出的MIMO探测器的吞吐量可达4.4Gbps。与其他设计相比，所提出的K-BEST探测器提供更大的吞吐量并执行卓越的硬件效率。
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