Multi-Dimension Resource Allocation for NOMA-Edge Computing-based 6G Power IoT

Abstract

Integrating edge computing and non-orthogonal multiple access (NOMA) into the 6G power Internet of Things (PIoT) provides a promising way to meet the stringent demands of communication delay, energy consumption, and massive connectivity. The service tasks can be partitioned into independent subtasks, and can be processed locally by PIoT devices or offloaded to the edge servers through reusing radio resource blocks (RBs). In this paper, we propose a Multi-timescale multi-dimEnsion Resource allocatIon and Task Splitting algorithm, namely MERITS, for NOMA-edge computing-based PIoT. First, Lyapunov optimization is exploited to decompose the long-term stochastic optimization problem into three short-term deterministic subproblems, i.e., RB allocation in a large timescale, task splitting and computation resource allocation in a small timescale. The first subproblem is modeled as a one-to-many matching problem with externalities, and solved by the proposed group-swap-matching based RB allocation algorithm. The second subproblem and third subproblem are relaxed into two continuous convex problem that can be solved easily. Simulation results demonstrate that MERITS outperforms the existing resource allocation and task splitting algorithms in terms of energy consumption, queue backlog, and complexity in the massive connectivity scenario.