Low-Complexity Dynamic Resource Scheduling for Downlink MC-NOMA Over Fading Channels

In this paper, we investigate dynamic resource scheduling (i.e., joint user, subchannel, and power scheduling) for downlink multi-channel non-orthogonal multiple access (MC-NOMA) systems over time-varying fading channels. Specifically, address the weighted average sum rate maximization problem with quality-of-service (QoS) constraints. particular, to facilitate fast scheduling, focus on developing a very low-complexity algorithm. To end, by leveraging Lagrangian duality stochastic optimization theory, first develop an opportunistic MC-NOMA algorithm whereby original is decomposed into series of subproblems, one each time slot. Accordingly, works in online manner solving subproblem per slot, making it more applicable practical systems. Then, further heuristic subchannel assignment allocation (Joint-SAPA) low computational complexity, called Joint-SAPA-LCC, that solves subproblem. Finally, through simulation, show our Joint-SAPA-LCC provides good performance comparable existing Joint-SAPA algorithms despite requiring much lower complexity. We also demonstrate which embedded well while satisfying given QoS requirements.