Queuing Analysis of Energy Harvesting-Aided NOMA-MEC Network

Non-orthogonal multiple access (NOMA) and energy harvesting (EH) have emerged as promising technologies to improve the energy efficiency and capacity of mobile edge computing (MEC) network. In this network, the mobile users utilize harvested energy to support the tasks computed locally or offloaded to MEC server through NOMA transmission. We propose an analytical framework to comprehensively explore the performance of the task processing procedure under EHaided NOMA-MEC network. Specifically, taking into account the EH constraint, local computing capacity, and NOMA offloading constraint, a four-dimensional Markov chain is introduced to model the task processing in each mobile user. To obtain the steady state of this Markov chain, we employ queuing theory to construct a discrete-time Geo/G/1 queue. By deriving the successful computation probability and the successful offloading probability, the mean response time for task completion is derived, which is a critical performance metric for the network. Numerical simulations are provided to verify the accuracy and facilitate the performance of the proposed framework.