Abstract
In this paper, we propose a novel energy efficiency maximization scheme for social-aware device-to-device (D2D) communications based on a genetic algorithm (GA). The proposed scheme incorporates both social and physical parameters of users to model the energy efficiency maximization problem. The formulated problem considers the spectral reuse, spectral efficiency, and the transmit power constraints of both cellular and D2D users to satisfy their quality of service requirements. Moreover, an algorithm based on the self-adaptive penalty function is applied to convert the constrained problem into an unconstrained problem. Next, GA is utilized to maximize the unconstrained problem. The feasibility of the proposed scheme is shown by computing its time complexity in terms of big- $O$ notation. Moreover, the convergence of the proposed scheme is analyzed by comparing the maximum and average values of the overall energy efficiencies for different iterations. Likewise, the performance is evaluated in terms of overall energy efficiency and system throughput for various D2D communications scenarios. To demonstrate the efficiency of the proposed scheme, the results are compared with those for a static penalty-based GA algorithm. Furthermore, to demonstrate the significance of combining the two types of parameters (i.e., social and physical), the performance of the proposed scheme is compared with schemes based on only social or physical parameters.
Highlights
The enormous growth in demand for multimedia and other social networking services and applications has significantly increased the network load on the current cellular communication system [1], [2]
Differing from the studies discussed in the previous subsection, we propose a social-aware energy efficiency scheme based on genetic algorithm (GA) with a self-adaptive penalty function algorithm for constraint handling
WORK we propose a novel algorithm for energy efficiency maximization in social-aware D2D communications
Summary
The enormous growth in demand for multimedia and other social networking services and applications has significantly increased the network load on the current cellular communication system [1], [2]. 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. Device-to-device (D2D) communications have emerged as a promising offloading solution as it enables the direct sharing of data between neighboring cellular devices with little assistance from the base station (BS) [5], [6]. This significantly alleviates the burden on the BS by offloading the traffic from proximity applications to direct communications
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