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Tree-Structured Random Vector Quantization for Beamforming in a Multiantenna Channel

机译:在多亮度通道中波束形成的树结构随机矢量量化

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摘要

A point-to-point multiantenna wireless channel is considered. Based on channel information, a receiver selects a transmit beamforming vector, which contains transmit antenna gains, from a vector set or codebook. The codebook index for the selected beamforming vector that maximizes channel capacity is relayed to the transmitter via a rate-limited feedback channel. Previously, we have proposed a Random Vector Quantization (RVQ) codebook, which consists of independent isotropically distributed vectors and showed that it performs close to the optimal codebook. However, RVQ requires exhaustive search to locate the desired beamformer. To lessen the search complexity, we propose a tree-structured (TS) RVQ. Numerical results show that number of computations required for TS-RVQ search can be orders of magnitude fewer than that required for RVQ search for given performance.
机译:考虑点对点的多生物天线无线信道。基于信道信息,接收器从向量集或码本中选择包含发射天线增益的发送波束成形向量。最大化信道容量的所选波束成形矢量的码本索引通过速率有限的反馈信道中继到发射机。以前,我们提出了一个随机向量量化(RVQ)码本,其包括独立的各向同性分布式矢量,并显示它靠近最佳码本。但是,RVQ需要详尽的搜索来定位所需的波束形成器。要减少搜索复杂性,我们提出了一种树结构(TS)RVQ。数值结果表明,TS-RVQ搜索所需的计算数量可以是比RVQ搜索对给定性能所需的数量级。

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