Blockchain and AI Enabled Configurable Reflection Resource Allocation for IRS-Aided Coexisting Drone-Terrestrial Networks

With the capability of establishing line-of-sight (LoS) links for devices, drones are generally utilized as aerial base stations to construct coexisting drone-terrestrial networks (CDTNs) for wireless communication. However, the established LoS links are easily blocked, thereby severely decreasing transmission performance. The intelligent reflecting surface (IRS) is a promising technology to improve data transmission in the CDTN by programming propagation channels. However, secure IRS reflection resource allocation is still an open issue. Existing IRS resource allocation methods are mainly based on a centralized third party and are vulnerable to the single point of failure. Furthermore, intelligent allocation of IRS reflection resources is also a key issue. To solve these problems, we propose a blockchain and artificial intelligence (AI) enabled configurable reflection resource allocation approach for the IRS-aided CDTN. First, we establish the IRS-aided communication framework for the CDTN, where a drone-mounted IRS is introduced to improve spatial freedom for data transmission. Second, the blockchain-based reflection resource management mechanism is proposed. In this mechanism, we design allocation transactions, the hierarchical blockchain structure, and smart-contract-enabled resource trading. Third, the AI-based reflection resource allocation mechanism is proposed, including the intelligent reflection elements assignment and deep-reinforcement-learning-driven reflection coefficient configuration. Furthermore, experimental results verify the effectiveness of our proposed approach. Finally, open issues and key challenges of the proposed approach are discussed.

Introduction

With features of flexible deployment and high agility, drones have attracted great attention in wireless communication fields. Drones have the capability to establish light-of-sight (LoS) wireless links for devices in harsh environments, such as emergency situation and areas without communication infrastructure [1]–[3]. Therefore, drones are widely applied as aerial base stations (BS) to support the current terrestrial communication, integrating as the coexisting drone-terrestrial network (CDTN) [4]. However, the LoS wireless links established by drones are easily blocked, which severely reduces the transmission performance.