Recently, there is a growing interest in achieving integrated sensing and communication (ISAC) in the sixth-generation (6G) cellular network. Inspired by this trend and the success of cooperative communication in cloud radio access network, this paper considers a networked device-free sensing architecture based on base station (BS) cooperation to transform the cellular network into a huge sensor that can provide ubiquitous and high-performance sensing services. Under this framework, the BSs first transmit the downlink communication signals to the mobile users and then estimate the range information of the targets based on their echoes. Next, a central processor collects the range information from all the BSs via the fronthaul links and localizes each target based on its distances to various BSs. To enable the above strategy in the 6G network, we will perform joint data association, non-line-of-sight (NLOS) mitigation, and clutter suppression, such that the central processor is able to find out the useful range estimations extracted from the line-of-sight (LOS) paths and match them to the right targets for localization. Numerical results show that our interested networked device-free sensing scheme for the 6G network can localize the targets with high accuracy in the challenging multi-path propagation environment.

翻译：近年来，在第六代（6G）蜂窝网络中实现通感一体化（ISAC）的需求日益增长。受此趋势及云无线接入网络中协作通信成功的启发，本文提出一种基于基站协作的网络化无设备感知架构，旨在将蜂窝网络改造为能够提供泛在且高性能感知服务的巨型传感器。在该框架下，基站首先向下行用户发送通信信号，并基于回波估计目标距离信息；随后，中央处理器通过前传链路收集所有基站的距离估计值，并依据各目标与不同基站间的距离实现定位。为在6G网络中实现上述策略，本文开展联合数据关联、非视距（NLOS）缓解与杂波抑制研究，以使中央处理器能够从视距（LOS）路径中提取有效距离估计，并将其匹配至正确目标以完成定位。数值结果表明，本文提出的面向6G网络的网络化无设备感知方案能够在复杂的多径传播环境中实现高精度目标定位。