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首页> 外文会议>2012 International Conference on Wireless Communications amp; Signal Processing >An improved LR-aided K-best algorithm for MIMO detection
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An improved LR-aided K-best algorithm for MIMO detection

机译：一种用于MIMO检测的改进的LR辅助K最优算法

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摘要

Recently, lattice reduction (LR) technique has caught great attention for multi-input multi-output (MIMO) receiver because of its low complexity and high performance. However, when the number of antennas is large, LR-aided linear detectors and successive interference cancellation (SIC) detectors still exhibit considerable performance gap to the optimal maximum likelihood detector (MLD). To enhance the performance of the LR-aided detectors, the LR-aided K-best algorithm was developed at the cost of the extra complexity on the order O(N2tK + NtK2), where Nt is the number of transmit antennas and K is the number of candidates. In this paper, we develop an LR-aided K-best algorithm with lower complexity by exploiting a priority queue. With the aid of the priority queue, our analysis shows that the complexity of the LR-aided K-best algorithm can be further reduced to O(N2tK + NtKlog2(K)). The low complexity of the proposed LR-aided K-best algorithm allows us to perform the algorithm for large MIMO systems (e.g., 50×50 MIMO systems) with large candidate sizes. Simulations show that as the number of antennas increases, the error performance approaches that of AWGN channel.
机译：近年来，晶格简化（LR）技术因其低复杂度和高性能而引起了多输入多输出（MIMO）接收器的极大关注。但是，当天线数量很大时，LR辅助线性检测器和连续干扰消除（SIC）检测器与最佳最大似然检测器（MLD）相比仍然表现出相当大的性能差距。为了增强LR辅助检测器的性能，开发了LR辅助K最佳算法，其代价是复杂度为O（N 2 t K + N t K 2 ），其中N t 是发射天线的数量，K是候选天线的数量。在本文中，我们通过利用优先级队列来开发一种具有较低复杂度的LR辅助K-best算法。借助优先级队列，我们​​的分析表明，LR辅助的K-best算法的复杂度可以进一步降低为O（N 2 t K + N t Klog 2 （K））。所提出的LR辅助的K最佳算法的低复杂度允许我们执行具有大候选尺寸的大型MIMO系统（例如50×50 MIMO系统）的算法。仿真表明，随着天线数量的增加，其误码性能接近AWGN信道。

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