Effective Energy Efficiency Computation Offloading in NOMA-Based MEC Networks with Delay Violation Probability Guarantee

We investigate the joint communication and computation problem in non-orthogonal multiple access based mobile edge computation networks for massive intelligent machine type communication. We model the whole task offloading process as a double tandem queues model and formulate an optimization problem to maximize effective energy efficiency while guaranteeing the End-to-End delay violation probability. To solve this problem, we propose a Joint Transmission Power allocation and Computation Resources allocation (JTPCR) algorithm. Specifically, we first minimize the task processing delay to obtain the optimal computation resource constrained by total computation resources and maximum tolerable delay. In addition, we exploit the Dinkelbach method to solve the fractional programming problem when optimizing the transmission power. We introduce an auxiliary variable and obtain the lower bounding concave approximation of channel capacity through a path-following method. Finally, we propose the alternating direction method of the multipliers to obtain the optimal transmission power. Simulation results show that the proposed JTPCR algorithm outperforms the comparison schemes under both scenarios: finite transmission blocklength and infinite transmission blocklength.