Distributed Artificial Intelligence Solution for D2D Communication in 5G Networks

Abstract

Device-to-device (D2D) communication, a core technology component of the evolving fifth-generation (5G) architecture, promises improvements in energy efficiency, spectral efficiency, overall system capacity, and higher data rates. These improvements in network performance spearheaded a vast amount of research in D2D, which identified significant challenges that need to be addressed before realizing their full potential in 5G networks, and beyond. Toward this end, this article proposes the use of a distributed intelligent approach to control the generation of D2D networks. More precisely, the proposed approach uses Belief Desire Intention (BDI) intelligent agents with extended capabilities (BDIx) to manage each D2D node independently and autonomously, without the help of the base station. To illustrate the above, this article proposes the DAIS algorithm for the decision of transmission mode in D2D, which maximizes the data rate and minimizes the power consumption in the network, while taking into consideration the computational load. Simulations show the applicability of BDI agents in solving D2D challenges.