Research Article
Performance Analysis of Mobile Edge Computing Network Applied Uplink NOMA with RF Energy Harvesting
@INPROCEEDINGS{10.1007/978-3-030-77424-0_6, author={Van-Truong Truong and Minh-Thong Vo and Dac-Binh Ha}, title={Performance Analysis of Mobile Edge Computing Network Applied Uplink NOMA with RF Energy Harvesting}, proceedings={Industrial Networks and Intelligent Systems. 7th EAI International Conference, INISCOM 2021, Hanoi, Vietnam, April 22-23, 2021, Proceedings}, proceedings_a={INISCOM}, year={2021}, month={5}, keywords={Mobile edge computing Non-orthogonal multiple access Uplink NOMA Successful computation probability MEC server Genetic algorithm Optimization}, doi={10.1007/978-3-030-77424-0_6} }- Van-Truong Truong
Minh-Thong Vo
Dac-Binh Ha
Year: 2021
Performance Analysis of Mobile Edge Computing Network Applied Uplink NOMA with RF Energy Harvesting
INISCOM
Springer
DOI: 10.1007/978-3-030-77424-0_6
Abstract
In this paper, we study a mobile edge computing (MEC) network based on uplink non-orthogonal multiple access (NOMA) scheme with radio frequency energy harvesting (RF EH). Due to the energy and compute resources constraint, two users cannot complete their tasks by themselves within the maximum time delay. Therefore, they harvest the RF energy from a nearby access point (AP) and use all that energy to offload their tasks to the AP. We derive the closed-form expressions of the successful computation probability (SCP) of the users to evaluate system performance. We propose a algorithm based on genetic algorithm (GA) that determines the system’s optimal time switching ratio to achieve the maximum SCP, namely MSCP-GA. Furthermore, we consider the numerical results to thoroughly understand the impact of parameters such as transmit power, time switching ratio on the system performance. Monte Carlo simulation is used to confirm the validity of our analysis.
