Online User and Power Allocation in Dynamic NOMA-Based Mobile Edge Computing

This study tackles the online user allocation problem in mobile edge computing (MEC) systems powered by non-orthogonal multiple access. App vendors need to determine a proper wireless channel in a base station/edge server and sufficient transmit power for every user. We consider a stochastic MEC system where users arrive and depart over time. When an edge server runs out of computing resources, some users will have to wait until the resources become available again, which incurs an allocation delay cost. This cost is often not investigated in many studies, which also do not consider a multi-cell, multi-channel system as we do in this work, due to its complexity. We aim to minimize the allocation delay and transmit power costs, increasing the system's energy efficiency. To achieve this objective while guaranteeing users' data rate requirements over time, we adopt the Lyapunov framework to convert this long-term optimization problem into a series of subproblems to be solved in every time slot. To solve the aforementioned subproblems efficiently, we present a distributed game theory-based approach. The proposed algorithm is theoretically evaluated and experimentally demonstrated to outperform several baseline and state-of-the-art methods, highlighting the significance of systematic consideration for both computation and communication aspects of this problem.