Intelligent Surface Empowered Sensing and Communication: A Novel Mutual Assistance Design

Meng, Kaitao; Wu, Qingqing; Matricardi, Elisabetta

doi:10.1109/lcomm.2023.3279142

Cited by 7 publications

(1 citation statement)

References 12 publications

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“…In this case, the number of intersections inevitably increases exponentially with respect to the number of targets, making it computationally expensive to determine which intersections are real targets or "ghost/shadow" targets [14], [15]. Second, radar cross sections (RCS) of served moving targets (e.g., vehicles) in urban environments are generally small, and the power of the transmitter may be limited, thus leading to weak echo signals and failure of precise target detection/tracking [16]. Finally, when the trajectories of several targets are in close proximity to each other, even with sufficient BSs, conventional localization methods have difficulty in discriminating these targets.…”

Section: Introductionmentioning

confidence: 99%

Cooperative Cellular Localization With Intelligent Reflecting Surface: Design, Analysis and Optimization

Meng,

Wu,

Chen

et al. 2024

IEEE Trans. Commun.

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Autonomous driving and intelligent transportation applications have dramatically increased the demand for highaccuracy and low-latency localization services. While cellular networks are potentially capable of target detection and localization, achieving accurate and reliable positioning faces critical challenges. Particularly, the relatively small radar cross sections (RCS) of moving targets and the high complexity for measurement association give rise to weak echo signals and discrepancies in the measurements. To tackle this issue, we propose a novel approach for multi-target localization by leveraging the controllable signal reflection capabilities of intelligent reflecting surfaces (IRSs). Specifically, IRSs are strategically mounted on the targets (e.g., vehicles and robots), enabling effective association of multiple measurements and facilitating the localization process. We aim to minimize the maximum Cramér-Rao lower bound (CRLB) of targets by jointly optimizing the target association, the IRS phase shifts, and the dwell time. However, solving this CRLB optimization problem is non-trivial due to the non-convex objective function and closely coupled variables. For single-target localization, a simplified closed-form expression is presented for the case where base stations (BSs) can be deployed flexibly, and the optimal BS location is derived to provide a lower performance bound of the original problem. Then, we prove that the transformed problem is a monotonic optimization, which can be optimally solved by the Polyblock-based algorithm. Moreover, based on derived insights for the single-target case, we propose a heuristic algorithm to optimize the target association and time allocation for the multi-target case. Furthermore, we provide useful guidance for the practical implementation of the proposed localization scheme by theoretically analyzing the relationship between time slots, BSs, and targets. Simulation results verify that deploying IRS on vehicles and effective phase shift design can effectively improve the resolution ability of multi-vehicle positioning and reduce the requirements of the number of BSs.

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Section: Introductionmentioning

confidence: 99%

Cooperative Cellular Localization With Intelligent Reflecting Surface: Design, Analysis and Optimization

Meng,

Wu,

Chen

et al. 2024

IEEE Trans. Commun.

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Vehicle-Mounted Intelligent Surface for Cooperative Localization in Cellular Networks

Meng,

Wu,

Chen

et al. 2023

2023 IEEE Globecom Workshops (GC Wkshps)

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Due to the continuous increase in the communication frequency band of the sixth-generation (6G) wireless communication network, it can potentially provide positioning services for applications such as intelligent transportation. However, limited radar cross sections of vehicles may result in too weak echo signals and incorrect measurement associations, especially for base stations (BSs) with low transmit power. To tackle this issue, we propose a novel cooperative localization scheme in cellular networks, where the controllable signal reflection capabilities of intelligent reflecting surfaces (IRSs) are utilized to facilitate target association. Specifically, IRSs are mounted on the vehicles to enhance the echo signals towards the associated BS while reducing interference with other BSs. We aim to minimize the maximum Cramér-Rao lower bound (CRLB) of location errors by jointly optimizing target association, IRS phase shifts, and dwell time. However, solving this CRLB optimization problem is non-trivial due to the non-convex objective function. To this end, we transform the problem for single-vehicle localization into a monotonic optimization problem, thereby optimally solving it through the Polyblock-based algorithm. For multi-vehicle localization, we propose a heuristic algorithm to efficiently optimize the target association and dwell time allocation. Finally, our simulation results verify that deploying IRSs on vehicles can effectively improve the resolution ability of multi-vehicle positioning and reduce the BS number requirements.

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Intelligent Surfaces Empowered Wireless Network: Recent Advances and the Road to 6G

Wu,

Zheng,

You

et al. 2024

Proc. IEEE

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Intelligent Surface Empowered Sensing and Communication: A Novel Mutual Assistance Design

Cited by 7 publications

References 12 publications

Cooperative Cellular Localization With Intelligent Reflecting Surface: Design, Analysis and Optimization

Cooperative Cellular Localization With Intelligent Reflecting Surface: Design, Analysis and Optimization

Vehicle-Mounted Intelligent Surface for Cooperative Localization in Cellular Networks

Intelligent Surfaces Empowered Wireless Network: Recent Advances and the Road to 6G

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