In the future 6G integrated sensing and communication (ISAC) cellular systems, networked sensing is a promising technique that can leverage the cooperation among the base stations (BSs) to perform high-resolution localization. However, a dense deployment of BSs to fully reap the networked sensing gain is not a cost-efficient solution in practice. Motivated by the advance in the intelligent reflecting surface (IRS) technology for 6G communication, this paper examines the feasibility of deploying the low-cost IRSs to enhance the anchor density for networked sensing. Specifically, we propose a novel heterogeneous networked sensing architecture, which consists of both the active anchors, i.e., the BSs, and the passive anchors, i.e., the IRSs. Under this framework, the BSs emit the orthogonal frequency division multiplexing (OFDM) communication signals in the downlink for localizing the targets based on their echoes reflected via/not via the IRSs. However, there are two challenges for using passive anchors in localization. First, it is impossible to utilize the round-trip signal between a passive IRS and a passive target for estimating their distance. Second, before localizing a target, we do not know which IRS is closest to it and serves as its anchor. In this paper, we show that the distance between a target and its associated IRS can be indirectly estimated based on the length of the BS-target-BS path and the BS-target-IRS-BS path. Moreover, we propose an efficient data association method to match each target to its associated IRS. Numerical results are given to validate the feasibility and effectiveness of our proposed heterogeneous networked sensing architecture with both active and passive anchors.

翻译：在未来的6G通感一体化（ISAC）蜂窝系统中，网络感知是一项极具前景的技术，它能够利用基站间的协作实现高精度定位。然而，在实际中，为充分获取网络感知增益而密集部署基站并非经济高效的解决方案。受第六代移动通信中智能反射面（IRS）技术进展的启发，本文探讨了通过部署低成本IRS来提升网络感知锚点密度的可行性。具体而言，我们提出了一种新颖的异构网络感知架构，该架构同时包含主动锚点（即基站）与被动锚点（即IRS）。在此框架下，基站发射下行正交频分复用（OFDM）通信信号，基于经IRS反射或未经IRS反射的目标回波实现目标定位。然而，采用被动锚点进行定位面临两大挑战：首先，无法利用被动IRS与被动目标之间的往返信号来估计二者距离；其次，在定位目标前，我们无法确定哪个IRS离目标最近并作为其锚点。本文证明，基于基站-目标-基站路径与基站-目标-IRS-基站路径的长度，可间接估计目标与其关联IRS之间的距离。此外，我们提出了一种高效的数据关联方法，用于将每个目标匹配到其对应的IRS。数值结果验证了所提出的含主动与被动锚点的异构网络感知架构的可行性与有效性。