A Social-Aware Resource Allocation for 5G Device-to-Device Multicast Communication

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Abstract
With the ever-increasing demands for popular content sharing among humans, device-to-device (D2D) multicast communication, as a promising technology to support wireless services within a local area, is introduced in a 5G cellular network. However, the existing resource allocation approaches for D2D multicast communication usually consider only physical domain constraints but neglect social domain factors, which would result in ineffective D2D links between users unwilling to share interests. Different from existing works, the D2D multicast scheme proposed in this paper will produce effective D2D multicast links by sufficiently utilizing both the physical and social properties of mobile users, with the goal to maximize the throughput of the overall social-aware network and guarantee fairly allocation of the channel between different D2D multicast clusters. The scheme mainly consists of two parts, the formation of D2D multicast clusters and joint optimization of power and channel allocation. In the formation of D2D multicast clusters, members and head in each cluster are selected by taking into account both social attributes and physical factors, such as community, ties, and geographical closeness. In the joint optimization, a two-step scheme is designed to first calculate the optimal power allocation by geometric proximity and then select suitable cellular channels for each D2D multicast cluster utilizing an extended one-to-many bipartite graphs matching algorithm. Simulation results demonstrate that, compared with heuristic algorithm and stochastic algorithm, the proposed scheme can increase the throughput of the overall social-aware network by about 5% and 50%, respectively.
Funding Information
  • National Natural Science Foundation of China (61271187)
  • China Postdoctoral Science Foundation (2017M610827)

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