3 research outputs found
Low-complexity joint user and power scheduling in downlink NOMA over fading channels
Non-orthogonal multiple access (NOMA) has been considered one of the most
promising radio access techniques for next-generation cellular networks. In
this paper, we study the joint user and power scheduling for downlink NOMA over
fading channels. Specifically, we focus on a stochastic optimization problem to
maximize the weighted average sum rate while ensuring given minimum average
data rates of users. To address this problem, we first develop an opportunistic
user and power scheduling algorithm (OUPS) based on the duality and stochastic
optimization theory. By OUPS, the stochastic problem is transformed into a
series of deterministic ones for the instantaneous weighted sum rate
maximization for each slot. Thus, we additionally develop a heuristic algorithm
with very low computational complexity, called user selection and power
allocation algorithm (USPA), for the instantaneous weighted sum rate
maximization problem. Via simulation results, we demonstrate that USPA provides
near-optimal performance with very low computational complexity, and OUPS well
guarantees given minimum average data rates.Comment: 7 pages, 5 figure
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, 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