Distributed Artificial Intelligence Solution for D2D Communication in 5G Networks

Abstract

Device to Device (D2D) Communication is one of the technology components of the evolving 5G architecture, as it promises improvements in energy efficiency, spectral efficiency, overall system capacity, and higher data rates. The above noted improvements in network performance spearheaded a vast amount of research in D2D, which have identified significant challenges that need to be addressed before realizing their full potential in emerging 5G Networks. Towards this end, this paper 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. This paper proposes the DAIS algorithm for the decision of transmission mode in D2D, which maximizes the data rate and minimizes the power consumption, while taking into consideration the computational load. Simulations show the applicability of BDI agents in solving D2D challenges.