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首页> 外文期刊>IEEE transactions on very large scale integration (VLSI) systems >Efficient Architecture for Soft-Input Soft-Output Sphere Detection With Perfect Node Enumeration
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Efficient Architecture for Soft-Input Soft-Output Sphere Detection With Perfect Node Enumeration

机译:具有完美节点枚举的软输入软输出球面检测的高效架构

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The application of the turbo principle allows to exploit the full potential of multiple-input multiple-output (MIMO) communications at the cost of increasing the computational effort at the receiver. In the context of soft-input soft-output tree search detection, the computation of metric values and the optimal node order represents two of the most computationally demanding operations. Heuristic approaches may be applied to reduce the complexity, but their accuracy is compromised by the effect that the input soft information has on the node ordering. The design of adaptive, good-performing, and cost-effective tree search detectors for iterative receivers represents, hence, a challenging task. To alleviate these complexity and performance loss drawbacks, an efficient MIMO sphere detector realization is proposed in this paper. A novel smart-sorting enumeration approach offers a significant gain in terms of throughput (from 40% up to a factor 5) and energy efficiency (up to 80% energy saving in the low SNR regime) with regard to preceding implementations. Owing to the additional low delay and area cost reported, the proposed design represents a very promising candidate toward a fast, accurate, and efficient MIMO detector.
机译:Turbo原理的应用允许以增加接收机的计算量为代价来开发多输入多输出(MIMO)通信的全部潜力。在软输入软输出树搜索检测的上下文中,度量值的计算和最佳节点顺序代表了两个计算量最大的操作。可以应用启发式方法来降低复杂性,但是其输入的软信息对节点排序的影响会影响其准确性。因此,针对迭代接收器的自适应,性能良好且具有成本效益的树搜索检测器的设计代表了一项艰巨的任务。为了减轻这些复杂性和性能损失的缺点,本文提出了一种有效的MIMO球检测器实现。相对于先前的实现方式,一种新颖的智能分类枚举方法在吞吐量(从40%到因子5)和能源效率(在低SNR情况下节省多达80%的能源)方面提供了显着的收益。由于报告了额外的低延迟和面积成本,因此提出的设计代表了朝着快速,准确和高效的MIMO检测器发展的极有希望的候选方案。

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