Social-Aware Peer Selection for Device-to-Device Communications in Dense Small-Cell Networks

Abstract

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.

Genetic Algorithm-Based Energy Efficiency Maximization for Social-Aware Device-to-Device Communications

“…1) In our previous study related to social-aware D2D peer selection, we computed the "cumulative closeness coefficient" (i.e., Δ), which combines the social and physical parameters of D2D users [4]. Herein, we use the computed Δ to derive the signal-to-noise plus interference ratio (SINR) and data rate for D2D users [25].…”

“…Herein, we use the computed Δ to derive the signal-to-noise plus interference ratio (SINR) and data rate for D2D users [25]. Moreover, we utilized the "social closeness coefficient" (i.e.,  ) proposed in [4] to calculate the power consumption coefficient of cellular (i.e.,  ) and D2D (i.e.,  ) users [26]. We use these parameters to derive the energy efficiencies for cellular and D2D users.…”

“…The social parameters utilized in our proposed scheme include Social Friendship Index, Social Closeness Index, and Interest Similarity Index. We follow the definitions of these parameters done in [4]. Likewise, the PPL characterizes the physical and network parameters of the users, ensuring physical proximity of users, which is a basic requirement for D2D communications.…”

“…Since the number of interconnected devices is expected to exceed three times the global population by the year 2023, this trend will continue [3]. Despite advancements in networking and radio access technologies, the current cellular communications system is struggling to fulfill its rapidly increasing requirements [4]. This has motivated the need to offload cellular traffic in the 5G system.…”

Green Communications in Smart Cities

“…In 5G communication systems with a large number of small cells, such techniques can reduce the backhaul communication requirements and reduce latency. An efficient novel algorithm based on the social and physical channel characteristics of the users for peer selection in D2D communication is proposed in [5]. There is a wide choice of frequency bands in 5G communication systems.…”