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

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, as well as 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 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.

Introduction

With the commercialization of the fifth generation (5G) wireless network and the exploration and development of its applications in vertical industries, the vision of the sixth generation (6G) wireless network has gradually attracted wide attentions. 6G wireless networks introduce new application scenarios while proposing higher performance indicators, such as seamless global connectivity, higher spectral- and energy-efficient, ultra-reliable communications, security, etc. In conventional networks, the transceiver module is a symmetrical architecture with independent radio frequency (RF) chains with high energy consumption components, such as power amplifiers. Nevertheless, a large number of accessed devices in 6G networks will inevitably lead to a sharp increase in power consumption. Therefore, the realization of high data rate with significantly reduced energy consumption and implementation cost for 6G wireless networks is still imperative.