Two-Stage Resource Allocation in Reconfigurable Intelligent Surface Assisted Hybrid Networks via Multi-player Bandits

Abstract

This paper considers a resource allocation problem where several Internet-of-Things (IoT) devices send data to a base station (BS) with or without the help of the reconfigurable intelligent surface (RIS) assisted cellular network. The objective is to maximize the sum rate of all IoT devices by finding the optimal RIS and spreading factor (SF) for each device. Since these IoT devices lack prior information on the RISs or the channel state information (CSI), a distributed resource allocation framework with low complexity and learning features is required to achieve this goal. Therefore, we model this problem as a twostage multi-player multi-armed bandit (MPMAB) framework to learn the optimal RIS and SF sequentially. Then, we put forth an exploration and exploitation boosting (E2Boost) algorithm to solve this two-stage MPMAB problem by combining the ǫ-greedy algorithm, Thompson sampling (TS) algorithm, and non-cooperation game method. We derive an upper regret bound for the proposed algorithm, i.e., O(log 1+δ 2 T ), increasing logarithmically with the time horizon T . Numerical results show that the E2Boost algorithm has the best performance among the existing methods and exhibits a fast convergence rate. More importantly, the proposed algorithm is not sensitive to the number of combinations of the RISs and SFs thanks to the two-stage allocation mechanism, which can benefit high-density networks.Index Terms-Reconfigurable intelligent surface (RIS), Internet-of-Things (IoT), multi-player multi-armed bandit (MPMAB), Thompson sampling (TS), exploration and exploitation boosting (E2Boost) algorithm.

A Survey on Federated Learning for Reconfigurable Intelligent Metasurfaces-Aided Wireless Networks

“…In [132], the authors study the RA problem in a RIM-aided hybrid uplink network, maximizing the sum rate of all IoT devices by finding the optimal RIM configuration and long range (LoRa) spreading factor 2 for each device. In [133], a RA scheme is proposed in a STAR-RIM-aided orthogonal multiple access and NOMA network, where the transmission-reflection beamforming at the STAR-RIM and the RA policy at the access point are jointly optimized to maximize the achievable sum rate.…”

Intelligent Omni-Surfaces: Simultaneous Refraction and Reflection for Full-Dimensional Wireless Communications

“…The RIS is an engineered planar surface with multiple nearly passive sub-wavelength scattering elements that can manipulate the signals impinging on it. Such a manipulation of signals can be realized through configuring the states of, for example, positive intrinsic negative (PIN) diodes embedded in the surface [20]. By tuning the ON/OFF state of each PIN diode, the amplitude and phase of the scattered signals can be programmed as desired, enabling signal re-radiation toward the receiver (Rx) at decreased hardware cost and energy [21].…”

“…3) Numerical Results: The performance of the proposed IOS-aided multi-cell distributed beamforming scheme is evaluated in Figs. 20 and 21 (see [96] for details). Fig.…”