Pricing for Reconfigurable Intelligent Surface Aided Wireless Networks: Models and Principles

TL;DR

This paper explores pricing strategies in reconfigurable intelligent surface (RIS) aided wireless networks to balance interests of service providers and property owners, proposing models and game-theoretic solutions for efficient deployment.

Contribution

It introduces RIS pricing models, summarizes fundamentals, and demonstrates a Stackelberg game approach for utility maximization in RIS-assisted wireless networks.

Findings

Proposes comprehensive RIS pricing models.

Demonstrates a Stackelberg game for utility maximization.

Highlights open issues and future research directions.

Abstract

Owing to the recent advancements of meta-materials and meta-surfaces, the concept of reconfigurable intelligent surface (RIS) has been embraced to meet the spectral- and energy-efficient, and yet cost-effective solutions for the sixth-generation (6G) wireless networks. From an operational standpoint, RISs can be easily deployed on the facades of buildings and indoor walls. Albeit promising, in the actual network operation, the deployment of RISs may face challenges because of the willingness and benefits of RIS holders from the aspect of installing RISs on their properties. Accordingly, RIS-aided wireless networks are faced with a formidable mission: how to balance the wireless service providers (WSPs) and RIS holders in terms of their respective interests. To alleviate this deadlock, we focus on the application of pricing models in RIS-aided wireless networks in pursuit of a win-win solution for both sides. Specifically, we commence with a comprehensive introduction of RIS pricing with its potential applications in RIS networks, meanwhile the fundamentals of pricing models are summarized in order to benefit both RIS holders and WSPs. In addition, a Stackelberg game-based model is exemplified to illustrate the operation of utility-maximization pricing. Finally, we highlight open issues and future research directions of applying pricing models to the RIS-aided wireless networks.