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This paper designs a helper-assisted resource allocation strategy innon-orthogonal multiple access (NOMA)-enabled mobile edge computing (MEC)systems, in order to guarantee the quality of service (QoS) of theenergy/delay-sensitive user equipments (UEs). To achieve a tradeoff between theenergy consumption and the delay, we introduce a novel performance metric,called \emph{energy-delay tradeoff}, which is defined as the weighted sum ofenergy consumption and delay. The joint optimization of user association,resource block (RB) assignment, power allocation, task assignment, andcomputation resource allocation is formulated as a mixed-integer nonlinearprogramming problem with the aim of minimizing the maximal energy-delaytradeoff. Due to the non-convexity of the formulated problem with coupled and0-1 variables, this problem cannot be directly solved with polynomialcomplexity. To tackle this challenge, we first decouple the formulated probleminto a power allocation, task assignment and computation resource allocation(PATACRA) subproblem. Then, with the solution obtained from the PATACRAsubproblem, we equivalently reformulate the original problem as a discrete userassociation and RB assignment (DUARA) problem. For the PATACRA subproblem, aniterative parametric convex approximation (IPCA) algorithm is proposed. Then,based on the solution obtained from the PATACRA subproblem, we first model theDUARA problem as a four-sided matching problem, and then propose alow-complexity four-sided UE-RB-helper-server matching (FS-URHSM) algorithm.Theoretical analysis demonstrates that the proposed algorithms are guaranteedto converge to stable solutions with polynomial complexity. Finally, simulationresults are provided to show the superior performance of our proposed algorithmin terms of the energy consumption and the delay.

Energy-Delay Tradeoff in Helper-Assisted NOMA-MEC Systems: A Four-Sided Matching Algorithm