Wu Kai, Zhang Jian Andrew, Huang Xiaojing, Guo Yingjie Jay
Global Big Data Technology Centre (GBDTC), University of Technology Sydney (UTS), Sydney, NSW 2122, Australia.
Sensors (Basel). 2022 Feb 18;22(4):1613. doi: 10.3390/s22041613.
Joint communications and sensing (JCAS) has recently attracted extensive attention due to its potential in substantially improving the cost, energy and spectral efficiency of Internet of Things (IoT) systems that need both radio frequency functions. Given the wide applicability of orthogonal frequency division multiplexing (OFDM) in modern communications, OFDM sensing has become one of the major research topics of JCAS. To raise the awareness of some critical yet long-overlooked issues that restrict the OFDM sensing capability, a comprehensive overview of OFDM sensing is provided first in this paper, and then a tutorial on the issues is presented. Moreover, some recent research efforts for addressing the issues are reviewed, with interesting designs and results highlighted. In addition, the redundancy in OFDM sensing signals is unveiled, on which, a novel method is based and developed in order to remove the redundancy by introducing efficient signal decimation. Corroborated by analysis and simulation results, the new method further reduces the sensing complexity over one of the most efficient methods to date, with a minimal impact on the sensing performance.
联合通信与感知(JCAS)因其在大幅提高需要射频功能的物联网(IoT)系统的成本、能源和频谱效率方面的潜力,最近受到了广泛关注。鉴于正交频分复用(OFDM)在现代通信中的广泛适用性,OFDM感知已成为JCAS的主要研究课题之一。为了提高对一些限制OFDM感知能力但长期被忽视的关键问题的认识,本文首先对OFDM感知进行了全面概述,然后介绍了关于这些问题的教程。此外,回顾了最近为解决这些问题所做的一些研究工作,突出了有趣的设计和结果。此外,揭示了OFDM感知信号中的冗余,在此基础上,基于冗余开发了一种新颖的方法,通过引入有效的信号抽取来消除冗余。经分析和仿真结果证实,新方法在对感知性能影响最小的情况下,比迄今为止最有效的方法之一进一步降低了感知复杂度。