Utility-Aware Resource Allocation for Hybrid NOMA in MEC: A Matching-Coalition Game Approach

Abstract

The massive influx of uplink task offloading in Multi-access Edge Computing (MEC) systems poses a significant challenge to the capacity of wireless networks. This challenge highlights a fundamental trade-off between Orthogonal Multiple Access (OMA), which provides interference-free but spectrally inefficient communication, and Non-Orthogonal Multiple Access (NOMA), which enhances capacity at the cost of significant inter-user interference. To navigate this trade-off, we introduce a novel Hybrid NOMA (H-NOMA) framework that offers differentiated communication services. The framework allows users to choose between premium OMA channels for latency-sensitive tasks and shared NOMA channels for others, creating an economy where performance can be traded for cost. Within this framework, we formulate the resource allocation problem with the objective of maximizing the total system utility, defined as the sum of all individual user utilities, under budget, computation, and communication constraints. To solve this NP-hard problem, we devise a novel multi-stage game-theoretic algorithm, the Matching-Coalition Game with Coordinate Descent (MCGCD). Our approach synergistically combines matching theory for a fast and initial channel assignment, a cooperative coalition game to refine allocations by explicitly managing NOMA externalities, and a coordinate-descent-based algorithm for optimal power control. Extensive simulations demonstrate that our proposed algorithm significantly outperforms benchmark methods in improving system utility, reducing average task completion latency, and increasing the number of admitted tasks.