用于宽带毫米波通信的雷达彩虹波束:波束训练和跟踪

Gui Zhou;Moritz Garkisch;Zhendong Peng;Cunhua Pan;Robert Schober
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引用次数: 0

摘要

我们提出了一种新的集成传感和通信(ISAC)方案,该方案利用传感来辅助视光(LoS)环境中的通信,确保毫米波(mmWave)宽带系统的快速初始访问、无缝用户跟踪和不间断通信。利用真时间延迟器(TTDs)控制波束斜视效应来产生频率相关的雷达彩虹波束。这些波束同时覆盖整个角空间的用户,仅使用一个正交频分复用(OFDM)符号进行快速波束训练。提出了三种基于雷达彩虹波束的探测和估计方案,用于估计用户的方向、距离和速度,然后用于通信波束形成器的设计。第一种方案利用单天线雷达接收机和一组彩虹波束,但可能导致多普勒模糊。为了解决这一限制,引入了两种额外的方案,分别利用两组彩虹波束和一个多天线接收器。在此基础上,对所提出的检测和估计方案进行了扩展,通过选择OFDM子载波的不同子集来实现用户跟踪。这种方法消除了切换移相器和ttd的需要,这是现有跟踪方案通常需要的。仿真结果表明了所提出的基于彩虹波束的移动用户训练和跟踪方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Radar Rainbow Beams for Wideband mmWave Communication: Beam Training and Tracking
We propose a novel integrated sensing and communication (ISAC) scheme that leverages sensing to assist communication in light-of-sight (LoS) environments, ensuring fast initial access, seamless user tracking, and uninterrupted communication for millimeter wave (mmWave) wideband systems. True-time-delayers (TTDs) are utilized to generate frequency-dependent radar rainbow beams by controlling the beam squint effect. These beams cover users across the entire angular space simultaneously for fast beam training using just one orthogonal frequency-division multiplexing (OFDM) symbol. Three detection and estimation schemes are proposed based on radar rainbow beams for estimation of the users’ directions, distances, and velocities, which are then exploited for communication beamformer design. The first proposed scheme utilizes a single-antenna radar receiver and one set of rainbow beams, but may cause a Doppler ambiguity. To tackle this limitation, two additional schemes are introduced, utilizing two sets of rainbow beams and a multi-antenna receiver, respectively. Furthermore, the proposed detection and estimation schemes are extended to realize user tracking by choosing different subsets of OFDM subcarriers. This approach eliminates the need to switch phase shifters and TTDs, which is typically required for existing tracking schemes. Simulation results reveal the effectiveness of the proposed rainbow beam-based training and tracking methods for mobile users.
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