Combination of Throughput-Optimal Scheduling and Network Utility Maximization in NOMA Systems With Flow-Level Dynamics

被引:0
|
作者
Chen, Yunpei [1 ]
Zhu, Qi [1 ]
Guo, Caili [2 ]
Yuan, Yifei [3 ]
Feng, Chunyan [2 ]
机构
[1] Nanjing Univ Posts & Telecommun, Engn Res Ctr Hlth Serv Syst Based Ubiquitous Wire, Jiangsu Key Lab Wireless Commun, Minist Educ, Nanjing 210003, Peoples R China
[2] Beijing Univ Posts & Telecommun, Sch Informat & Commun Engn, Beijing Key Lab Network Syst Architecture & Conve, Beijing 100876, Peoples R China
[3] China Mobile Res Inst, Future Mobile Technol Lab, Beijing 100053, Peoples R China
关键词
NOMA; Wireless networks; Dynamic scheduling; Scheduling algorithms; Heuristic algorithms; Quality of service; Downlink; Throughput-optimality; network utility maximi- zation; non-orthogonal multiple access; suboptimal algorithm; NONORTHOGONAL MULTIPLE-ACCESS; EFFICIENT RESOURCE-ALLOCATION; WIRELESS NETWORKS; 5G SYSTEMS; PERFORMANCE; POWER; TRANSMISSION; INSTABILITY; ALGORITHM; DELAY;
D O I
10.1109/TVT.2023.3287282
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In wireless networks, the network queue stability (throughput-optimality) and the network utility maximization are two crucial tasks for network operators. Besides, new techniques of mobile communications, e.g. the non-orthogonal multiple access (NOMA), have emerged endlessly to meet coming challenges. In this article, we for the first time, investigate a downlink NOMA system with flow-level dynamics, where long-lived flows and short-lived flows exist simultaneously, and formulate an optimization problem of user selection and power allocation. We aim to maximize the network utility at each time slot and simultaneously guarantee the throughput-optimality, under the quality of service (QoS) constraints. Considering the practicability of algorithm, the suboptimal algorithm containing two stages, is proposed. And we analyze the complexity of proposed algorithm. In the performance evaluation, the benchmark algorithm is provided for comparison. And we take the energy efficiency (EE) as an example of the network utility and define the scheduling delay (SD). Simulation results show that the suboptimal algorithm is throughput-optimal, and understandably, its performances could be better than those in the benchmark algorithm in terms of EE and SD, as long as the appropriate parameter is set.
引用
收藏
页码:14573 / 14588
页数:16
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