SNR Scaling Laws for Radio Sensing with Extremely Large-Scale MIMO

Abstract

Mobile communication networks were designed to mainly support ubiquitous wireless communications, yet they are also expected to achieve radio sensing capabilities in the near future. However, most prior studies on radio sensing usually rely on far-field assumption with uniform plane wave (UPW) models. With the ever-increasing antenna size, together with the growing demands to sense nearby targets, the conventional far-field UPW assumption may become invalid. Therefore, this paper studies near-field radio sensing with extremely large-scale (XL) antenna arrays, where the more general uniform spheric wave (USW) sensing model is considered. Closed-form expressions of the Cramér-Rao Bounds (CRBs) for both angle and range estimations are derived for near-field XL-MIMO radar mode and XL-phased array radar mode, respectively. Our results reveal that different from the conventional UPW model where the CRB for angle decreases unboundedly as the number of antennas increases, for XL-MIMO radar-based near-field sensing, the CRB decreases with diminishing return and approaches to a certain limit as the number of antennas increases. Besides, different from the farfield model where the CRB for range is infinity since it has no range estimation capability, that for the near-field case is finite. Furthermore, it is revealed that the commonly used spherical wave model based on second-order Taylor approximation is insufficient for near-field CRB analysis. Extensive simulation results are provided to validate our derived CRBs.

Integrated Sensing and Communication with Delay Alignment Modulation: Performance Analysis and Beamforming Optimization

“…ISAC aims at efficiently utilizing the precious radio resources, hardware, and infrastructure platform to achieve dual functions of sensing and communication. Furthermore, mutualism between sensing and communication could also be achieved, say via sensingaided communication and communication-aided sensing enhancement [12]- [14].…”

Very large scale integration architectures of discrete transforms for digital signal processing applications

“…The authors in [206] investigated radar sensing using XL antenna arrays in mobile communication networks, introduc-ing a flexible model that accounts for both spherical wavefront and amplitude variations among array elements. This research surpasses conventional uniform plane wave (UPW) models.…”

“…It offers valuable insights for designing and implementing XL-MIMO radar and XL-phased-array radar modes in mobile networks [44]. In a related study, the authors in [207] investigated near-field radio sensing utilizing XL antenna arrays. Using a uniform spheric wave (USW) sensing model, they developed closed-form expressions for the Cramér-Rao Bounds (CRBs) for angle and range estimations in near-field XL-MIMO radar mode and XL-phased array radar mode [207].…”

“…In a related study, the authors in [207] investigated near-field radio sensing utilizing XL antenna arrays. Using a uniform spheric wave (USW) sensing model, they developed closed-form expressions for the Cramér-Rao Bounds (CRBs) for angle and range estimations in near-field XL-MIMO radar mode and XL-phased array radar mode [207]. This study highlights the practical limitations of antenna array size in nearfield sensing and provides insight into the tradeoffs between array size and estimation precision.…”

“…The performance of XL-MIMO systems can be substantially enhanced by employing machine learning and artificial intelligence techniques [207], [209]. This includes the development of intelligent channel estimation methods, beamforming strategies, user scheduling, and resource allocation schemes that adapt to the ever-changing wireless communication environment.…”