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Integrating Low-Complexity and Flexible Sensing Into Communication Systems
IEEE Journal on Selected Areas in Communications ( IF 16.4 ) Pub Date : 2022-03-04 , DOI: 10.1109/jsac.2022.3156649
Kai Wu 1 , J. Andrew Zhang 1 , Xiaojing Huang 1 , Y. Jay Guo 1
Affiliation  

Integrating sensing into standardized communication systems can potentially benefit many consumer applications that require both radio frequency functions. However, without an effective sensing method, such integration may not achieve the expected gains of cost and energy efficiency. Existing sensing methods, which use communication payload signals, either have limited sensing performance or suffer from high complexity. In this paper, we develop a novel and flexible sensing framework which has a complexity only dominated by a Fourier transform and also provides the flexibility in adapting to different sensing needs. We propose to segment a whole block of echo signal evenly into sub-blocks; adjacent ones are allowed to overlap. We design a virtual cyclic prefix (VCP) for each sub-block that allows us to employ two common ways of removing communication data symbols and generate two types of range-Doppler maps (RDMs) for sensing. We perform a comprehensive analysis of the signal components in the RDMs, proving that their interference-plus-noise (IN) terms are approximately Gaussian distributed. The statistical properties of the distributions are derived, which leads to the analytical comparisons between the two RDMs as well as between the prior and our sensing methods. Moreover, the impact of the lengths of sub-block, VCP and overlapping signal on sensing performance is analyzed. Criteria for designing these lengths for better sensing performance are also provided. Extensive simulations validate the superiority of the proposed sensing framework over prior methods in terms of signal-to-IN ratios in RDMs, detecting performance and flexibility.

中文翻译:

将低复杂性和灵活的传感集成到通信系统中

将传感集成到标准化通信系统中可能会使许多需要两种射频功能的消费者应用受益。然而,如果没有有效的传感方法,这种集成可能无法实现预期的成本和能源效率收益。使用通信有效载荷信号的现有传感方法要么具有有限的传感性能,要么具有高复杂性。在本文中,我们开发了一种新颖且灵活的传感框架,其复杂性仅由傅里叶变换主导,并且还提供了适应不同传感需求的灵活性。我们建议将整个回波信号块均匀地分割成子块;允许相邻的重叠。我们为每个子块设计了一个虚拟循环前缀 (VCP),它允许我们采用两种常用的方法来删除通信数据符号并生成两种类型的距离多普勒图 (RDM) 用于传感。我们对 RDM 中的信号分量进行了全面分析,证明它们的干扰加噪声 (IN) 项近似为高斯分布。导出了分布的统计特性,这导致了两个 RDM 之间以及先前和我们的传感方法之间的分析比较。此外,分析了子块长度、VCP长度和重叠信号长度对传感性能的影响。还提供了设计这些长度以获得更好的传感性能的标准。
更新日期:2022-03-04
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