Integrating Passive Bistatic Sensing into mmWave B5G/6G Networks: Design and Experiment Measurement

• Main Authors: Li, Songqian, Luo, Chenhao, Tang, Aimin, Wang, Xudong, Xu, Chaojun, Gao, Fei, Cai, Liyu
• Format: Conference Proceeding
• Language: English
• Subjects: Estimation; Half-duplex system; Location awareness; Prototypes; Radar tracking; Superresolution; Target tracking
• ISSN: 1938-1883
• DOI: 10.1109/ICC45041.2023.10279065

Recently, integrated sensing and communications (ISAC) design has attracted great attention for B5G/6G networks. Existing ISAC studies are mainly focused on monostatic sensing with a full-duplex radio. However, full-duplex radio requires complicated self-interference cancellations and many current devices are half-duplex radios. Therefore, it is still interesting to investigate passive bistatic sensing with half-duplex radios. In this paper, integrating passive bistatic sensing into mmWave B5G/6G networks is investigated. The public reference signals are leveraged to extract the frequency-domain channel state information (CSI) for passive sensing. To address the problems of sampling-timing-offset and random phase error, a line-of-sight (LoS) path aided calibration mechanism is first developed. To achieve accurate localization for multiple targets, a novel super-resolution channel impulse response (CIR) based mechanism is then developed. The super-resolution CIR is achieved from CSI through a joint design of spatial-smoothing multiple signal classification (MUSIC) algorithm and template-based tap estimation. With the super-resolution CIR, multiple targets can be first distinguished in CIR taps and then localized by further estimating their angle of arrivals (AoAs). The proposed design is implemented and validated on a prototype system at 28 GHz with 500 MHz bandwidth in indoor environments. Experimental results show that our design can achieve accurate single-target and multi-target localization and tracking. The localization error is 26 cm at 80 th percentile for single-person and 29 cm on average for multi-person setups. The average error to the planned path after the moving-averaged filter is 11 cm and 19 cm for single-person and two-person tracking, respectively.