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Robust Resource Allocation for RIS-Aided Multi-User SLAC System
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DOI：10.1109/TITS.2024.3474674.png)
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摘要
En 中文
This paper considers a reconfigurable intelligent surface (RIS)-aided multi-user simultaneous localization and communication (SLAC) system with statistical position uncertainty, where an RIS is deployed to simultaneously enhance the quality of service. To this end, we first derive the closed-form Cram & eacute;r-Rao lower bound concerning position parameters as the localization metric and also provide the achievable rate metric for communication services. Then, the joint robust design of subcarrier groups, beamforming vectors, and the phase-shift matrix of the RIS is formulated as a stochastic bi-objective optimization problem to maximize expected localization and communication metrics. Due to the nonlinearity of the multi-objective function and the coupling between optimizing variables, the resulting problem is highly non-convex. Accordingly, we transform the expected achievable rate into an analytical form and further develop a novel unified successive convex approximation (U-SCA)-based iterative algorithm to obtain a robust resource allocation strategy. In particular, we derive closed-form solutions of beamforming vectors and the phase-shift matrix of RIS to decrease the computational complexity. In addition, we also analyse the convergence of the proposed U-SCA-based algorithm. Simulation results demonstrate the effectiveness of the presented method.
Keyword:
Location awareness
Resource management
Reconfigurable intelligent surfaces
Measurement
Vectors
Optimization
Closed-form solutions
Bandwidth
Array signal processing
Hardware
Simultaneous localization and communication
reconfigurable intelligent surface
robust resource allocation
unified successive convex approximation
期刊
IF:
8.4
论文数:
9.6K
被引数:
6.3W
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