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Tree-Structured Random Vector Quantization for Limited-Feedback Wireless Channels

机译:有限反馈无线信道的树结构随机矢量量化

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摘要

We consider the quantization of a transmit beamforming vector in multiantenna channels and of a signature vector in code division multiple access (CDMA) systems. Assuming perfect channel knowledge, the receiver selects for a transmitter the vector that maximizes the performance from a random vector quantization (RVQ) codebook, which consists of independent isotropically distributed unit-norm vectors. The quantized vector is then relayed to the transmitter via a rate-limited feedback channel. The RVQ codebook requires an exhaustive search to locate the selected entry. To reduce the search complexity, we apply generalized Lloyd or k-dimensional (kd)-tree algorithms to organize RVQ entries into a tree. In examples shown, the search complexity of tree-structured (TS) RVQ can be a few orders of magnitude less than that of the unstructured RVQ for the same performance. We also derive the performance approximation for TS-RVQ in a large system limit, which predicts the performance of a moderate-size system very well.
机译:我们考虑在多天线信道中的发射波束成形矢量和在码分多址(CDMA)系统中的签名矢量的量化。假设具有完善的信道知识,则接收器会从随机向量量化(RVQ)码本中为发送器选择能使性能最大化的向量,该向量本由独立的各向同性分布的单位范式向量组成。然后,量化矢量通过速率受限的反馈信道中继到发射机。 RVQ码本需要详尽搜索以找到所选条目。为了减少搜索的复杂性,我们应用了广义的Lloyd或k维(kd)树算法来将RVQ条目组织到树中。在所示的示例中,对于相同的性能,树结构(TS)RVQ的搜索复杂度可以比非结构化RVQ的搜索复杂度小几个数量级。我们还可以在较大的系统限制中得出TS-RVQ的性能近似值,这可以很好地预测中等大小系统的性能。

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