Max-Min Fairness Optimization in 6G Sustainable Multi-Cell Transportation Systems Using Reconfigurable Intelligent Surfaces

초록

This paper addresses the challenge of enhancing spectral efficiency in multi-cell vehicular communication, where a base station (BS) in each cell reuses the available spectrum to serve multiple vehicles, leading to considerable cochannel interference. To mitigate these effects and improve communication in environments with frequent blockages, reconfigurable intelligent surfaces (RIS) are deployed within each cell to assist the signal delivery from BS to vehicles. This work investigates a fair resource allocation in a multi-cell vehicular scenario where spectrum reuse and inter-cell interference can severely degrade the worst-user performance. We formulate a max-min fairness optimization problem that maximizes the minimum achievable user rate/capacity by jointly optimizing the BS power allocation and RIS phase shifts in each cell under practical constraints. The simulation main contributions are as follows: (i) we propose a RIS-aided multi-cell vehicular framework and derive the corresponding SINR and worst-user performance metric under spectrum reuse; (ii) we develop an efficient alternating-optimization solution that decouples the original non-convex problem into a power-allocation subproblem solved via water-filling and a RIS phase-shift design subproblem handled via semidefinite relaxation (SDR); (iii) we analyze the convergence behavior and computational complexity of the proposed algorithm; and (iv) Simulation results show that the proposed design improves the average sum capacity by about 5-17% over the random RIS phase shift scheme and by about 29-50% over the benchmark scheme without RIS.

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