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, we address the weighted average sum rate maximization problem
with quality-of-service (QoS) constraints. In particular, to facilitate fast
resource scheduling, we focus on developing a very low-complexity algorithm. To
this end, by leveraging Lagrangian duality and the stochastic optimization
theory, we first develop an opportunistic MC-NOMA scheduling algorithm whereby
the original problem is decomposed into a series of subproblems, one for each
time slot. Accordingly, resource scheduling works in an online manner by
solving one subproblem per time slot, making it more applicable to practical
systems. Then, we further develop a heuristic joint subchannel assignment and
power allocation (Joint-SAPA) algorithm with very low computational complexity,
called Joint-SAPA-LCC, that solves each subproblem. Finally, through
simulation, we show that our Joint-SAPA-LCC algorithm provides good performance
comparable to the existing Joint-SAPA algorithms despite requiring much lower
computational complexity. We also demonstrate that our opportunistic MC-NOMA
scheduling algorithm in which the Joint-SAPA-LCC algorithm is embedded works
well while satisfying given QoS requirements.Comment: 39 pages, 11 figure
