Social-aware peer selection for device-to-device communications in dense small-cell networks

Device-to-device communications refer to the emerging paradigm that permits direct communication between cellular users that are in close physical and social proximity. It is expected to become an essential aspect of the future 5G cellular communications system. As a prerequisite for device-to-device communications, a user has to select another user in its proximity that has the desired information/service and is willing to share it. In this paper, we propose a method for peer selection in dense small-cell device-to-device networks that uses multi-attribute decision modeling. The method exploits both the physical and social characteristics of the user equipment to find the most suitable peer for device-to-device communications. We assume hexagonal small-cell and macro-cell architectures with a small-cell/macro-cell base station with multiple user equipments in its coverage area to evaluate the proposed scheme’s performance. The small-/macro-cell base station exploits various social and physical attributes to rank peers and selects the best one for device-to-device communication with the requesting user. The numerical results demonstrate the proposed algorithm’s efficiency in terms of computational time, selection of the best peer, throughput, and energy efficiency of device-to-device communications.