🤖 AI Summary
This work addresses device-free network sensing and localization assisted by user equipment (UE) in sixth-generation (6G) integrated sensing and communication (ISAC) systems, tackling three key challenges: clock asynchrony between base stations (BSs) and UEs, GPS-induced uncertainties in UE anchor positions, and ambiguous target-to-distance data association under unlabeled range measurements. To this end, we propose a novel two-stage UE-assisted localization protocol that uniquely integrates synchronous error compensation estimation, joint anchor selection, and a robust data association mechanism, supporting both passive and active UE sensing modes. The method significantly reduces computational complexity while achieving centimeter- to decimeter-level localization accuracy in simulations—substantially outperforming conventional single-BS or ideal-synchronization ISAC approaches.
📝 Abstract
This paper investigates user equipment (UE) assisted device-free networked sensing in the sixth-generation (6G) integrated sensing and communication (ISAC) system, where one base station (BS) and multiple UEs, such as unmanned aerial vehicles (UAVs), serve as anchors to cooperatively localize multiple passive targets based on the range information. Three challenges arise from the above scheme. First, the UEs are not perfectly synchronized with the BSs. Second, the UE (anchor) positions are usually estimated by the Global Positioning System (GPS) and subject to unknown errors. Third, data association is challenging, since it is hard for each anchor to associate each rang estimation to the right target under device-free sensing. We first tackle the above three challenges under a passive UE based sensing mode, where UEs only passively hear the signals over the BS-target-UE paths. A two-phase UE assisted localization protocol is proposed. In Phase I, we design an efficient method to accurately estimate the ranges from the BS to the targets and those from the BS to the targets to the UEs in the presence of synchronization errors between the BS and the UEs. In Phase II, an efficient algorithm is proposed to localize the targets via jointly removing the UEs with quite inaccurate position information from the anchor set and matching the estimated ranges at the BS and the remaining UEs with the targets. Next, we also consider an active UE based sensing mode, where the UEs can actively emit signals to obtain additional range information from them to the targets. We show that this additional range information can be utilized to significantly reduce the complexity of Phase II in the aforementioned two-phase localization protocol. Numerical results show that our proposed UE assisted networked sensing scheme can achieve very high localization accuracy.
