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Compressive Sensing-Based Beamforming for Millimeter-Wave OFDM Systems

机译：基于压缩感测的毫米波OFDM系统波束形成

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摘要

In this paper, we address codebook-based beamforming for multi-antenna orthogonal frequency division multiplexing (OFDM) systems operating in 60-GHz millimeter-wave band. Given a pre-specified codebook, the task of the beamforming process is to identify the best transmit and receive beam vectors to maximize the spectral efficiency. By properly modeling the multipath structure in 60-GHz channels, we transform the above task into the estimation of several sparse signal vectors. Furthermore, we tailor compressive sensing (CS) technology to efficiently estimate such sparse signals, wherein the CS measurement matrix is specifically designed by minimizing the inner products between different columns of the CS effective dictionary. As a result, CS-based iterative and non-iterative beamforming schemes are proposed. Due to the ability to judiciously exploit multipath sparsity inherent in 60-GHz channels, the proposed schemes significantly outperform the existing counterparts in terms of training overhead and success probability, which is confirmed by theoretical analysis and extensive simulations.
机译：在本文中，我们针对在60 GHz毫米波段工作的多天线正交频分复用（OFDM）系统解决了基于码本的波束形成问题。给定一个预先指定的密码本，波束成形过程的任务是确定最佳的发射和接收波束矢量，以最大化频谱效率。通过在60 GHz信道中正确建模多径结构，我们将上述任务转换为几种稀疏信号矢量的估计。此外，我们定制了压缩感知（CS）技术来有效地估计此类稀疏信号，其中CS测量矩阵是通过最小化CS有效字典的不同列之间的内积来专门设计的。结果，提出了基于CS的迭代和非迭代波束成形方案。由于能够明智地利用60 GHz信道固有的多径稀疏性，因此在训练开销和成功概率方面，所提出的方案明显优于现有的方案，这在理论分析和广泛的模拟中得到了证实。

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