Codebook Design for Millimeter-Wave Channel Estimation with Hybrid Precoding Structure
Zhenyu Xiao, Pengfei Xia, Xiang-Gen Xia

TL;DR
This paper introduces a new metric called GDP for evaluating and designing hierarchical codebooks for mmWave channel estimation with hybrid precoding, considering power constraints, and proposes two effective design solutions that outperform existing methods.
Contribution
It presents the first GDP metric for mmWave codebook design and proposes two novel hierarchical codebook design methods exploiting BMW-MS technique.
Findings
GDP effectively evaluates codeword quality.
BMW-MS/LCS and BMW-MS/CF outperform existing codebooks.
Proposed methods work well under per-antenna power constraints.
Abstract
In this paper, we study hierarchical codebook design for channel estimation in millimeter-wave (mmWave) communications with a hybrid precoding structure. Due to the limited saturation power of mmWave power amplifier (PA), we take the per-antenna power constraint (PAPC) into consideration. We first propose a metric, i.e., generalized detection probability (GDP), to evaluate the quality of \emph{an arbitrary codeword}. This metric not only enables an optimization approach for mmWave codebook design, but also can be used to compare the performance of two different codewords/codebooks. To the best of our knowledge, GDP is the first metric particularly for mmWave codebook design for channel estimation. We then propose an approach to design a hierarchical codebook exploiting BeaM Widening with Multi-RF-chain Sub-array technique (BMW-MS). To obtain crucial parameters of BMW-MS, we provide two…
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Taxonomy
TopicsMillimeter-Wave Propagation and Modeling · Microwave Engineering and Waveguides · Advanced MIMO Systems Optimization
