Low-Complexity Dynamic Resource Scheduling for Downlink MC-NOMA Over Fading Channels
Low-Complexity Dynamic Resource Scheduling for Downlink MC-NOMA Over Fading Channels
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DOI：
10.1109/twc.2021.3123298
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发表时间：
2021-03
影响因子：
10.4
通讯作者：
Do-Yup Kim;H. Jafarkhani;Jang-Won Lee
中科院分区：
文献类型：
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作者：
Do-Yup Kim;H. Jafarkhani;Jang-Won Lee
本文研究了时变衰落信道下下行多信道非正交多址(MC-NOMA)系统的动态资源调度(即联合用户、子信道和功率调度)。具体地说，我们研究了具有服务质量(Qos)约束的加权平均和速率最大化问题。特别是，为了便于快速的资源调度，我们专注于开发一种非常低复杂度的算法。为此，我们首先利用拉格朗日对偶和随机优化理论，提出了一种机会MC-NOMA调度算法，将原问题分解为一系列的子问题，每个子问题对应一个时隙。相应地，资源调度以在线方式工作，每个时隙解决一个子问题，使其更适用于实际系统。然后，我们进一步提出了一种计算复杂度非常低的启发式联合子信道分配和功率分配(Joint-SAPA)算法，称为Joint-SAPA-LCC，它解决了每个子问题。最后，通过仿真验证了本文提出的联合SAPA-LCC算法具有与已有的联合SAPA算法相当的性能，而计算复杂度却要低得多。我们还证明了我们的机会MC-NOMA调度算法，其中嵌入了联合SAPA-LCC算法，在满足给定的服务质量要求的同时工作得很好。
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.