Abstract:
Resource allocation in mobile edge computing (MEC)- based wireless networks with energy harvesting has attracted great attention. However, existing works assume that mobi...Show MoreMetadata
Abstract:
Resource allocation in mobile edge computing (MEC)- based wireless networks with energy harvesting has attracted great attention. However, existing works assume that mobile devices are stationary while harvesting energy. In this paper, an uplink resource allocation strategy is developed in MEC-based heterogeneous networks. A random mobility model is designed to describe the movement of the user equipment (UE). Meanwhile, the UE can harvest energy from six frequency bands while moving along a certain path. The energy harvesting model of the UE is given by an integral expression. The objective of the resource allocation problem is to maximize the energy efficiency (EE) under the constraints of energy consumption, total data rate requirement, sub-carrier allocation, and transmission power. A quantum-behaved particle swarm optimization (QPSO) algorithm is employed to obtain a sub-optimal solution. Numerical results show that the amount of energy harvested by the UE decreases as the moving speed increases. Moreover, the QPSO algorithm has higher EE than an existing particle swarm optimization algorithm.
Date of Conference: 20-24 May 2018
Date Added to IEEE Xplore: 30 July 2018
ISBN Information:
Electronic ISSN: 1938-1883