Resource allocation in RF energy harvesting‐assisted underlay D2D communication. Issue 7 (18th March 2019) - Yu, Shuo; Ejaz, Waleed; Guan, Ling; Anpalagan, Alagan; Rizvi, Imran A.
Abstract: Device to device (D2D) communication is capable to address the increasing demand for data rates in fifth generation (5G) and beyond networks. However, D2D communication is usually convoluted with interference scenarios since both D2D users and cellular users share the same spectrum resources. Furthermore, D2D systems can trace back to limited battery life. The battery life problem is becoming more challenging with the exponential increase of devices in the future networks. Therefore, efficient resource allocation schemes need investigation to offer better quality of service for both cellular and D2D users under the constraints of interference and energy. In this paper, we address these two problems (interference and energy) simultaneously by efficiently allocating resources in energy harvesting‐assisted underlay D2D communication. We propose a deterministic model in which D2D users harvest energy only when required. We propose a resource allocation scheme, which jointly allocate resources and transmit power. We formulate an optimization problem with an objective to maximize sum throughput of D2D system while satisfying constraints on quality of service, power, and interference. To solve the problem, we adopt the nonlinear optimization by mesh adaptive direct search algorithm to obtain the suboptimal solution. We show the effectiveness of the proposed scheme in comparison with existing algorithms through simulation results. Abstract : A deterministic model is proposed for energy harvesting‐assisted underlay D2D communication. An optimization problem is formulated to maximize sum throughput of all D2D users by efficient resource allocation and transmit power. The simulation results obtained using nonlinear optimization by mesh adaptive direct search (NOMAD) with channel‐based heuristic algorithm are compared with random resource allocation algorithm to highlight the advantages of both optimal and suboptimal solutions and computational time complexity is provided for both algorithms.