User Clustering and Power Allocation for Energy Efficiency Maximization in Downlink Non-Orthogonal Multiple Access Systems

被引:11
|
作者
Chen, Ruibiao [1 ]
Shu, Fangxing [1 ]
Lei, Kai [1 ]
Wang, Jianping [2 ]
Zhang, Liangjie [3 ]
机构
[1] Peking Univ, ICNLAB, Sch Elect & Comp Engn SECE, Shenzhen 518000, Peoples R China
[2] City Univ Hong Kong, Dept Comp Sci, Hong Kong 999077, Peoples R China
[3] Kingdee Software China Co Ltd, Shenzhen 518000, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2021年 / 11卷 / 02期
基金
中国国家自然科学基金;
关键词
energy efficiency maximization; non-orthogonal multiple access systems; Lagrangian multiplier method; inter-cluster dynamic programming; SUCCESSIVE INTERFERENCE CANCELLATION; MASSIVE MIMO; PERFORMANCE ANALYSIS; NOMA SYSTEMS; 5G SYSTEMS; NETWORKS; MINIMIZATION;
D O I
10.3390/app11020716
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Non-orthogonal multiple access (NOMA) has been considered a promising technique for the fifth generation (5G) mobile communication networks because of its high spectrum efficiency. In NOMA, by using successive interference cancellation (SIC) techniques at the receivers, multiple users with different channel gain can be multiplexed together in the same subchannel for concurrent transmission in the same spectrum. The simultaneously multiple transmission achieves high system throughput in NOMA. However, it also leads to more energy consumption, limiting its application in many energy-constrained scenarios. As a result, the enhancement of energy efficiency becomes a critical issue in NOMA systems. This paper focuses on efficient user clustering strategy and power allocation design of downlink NOMA systems. The energy efficiency maximization of downlink NOMA systems is formulated as an NP-hard optimization problem under maximum transmission power, minimum data transmission rate requirement, and SIC requirement. For the approximate solution with much lower complexity, we first exploit a quick suboptimal clustering method to assign each user to a subchannel. Given the user clustering result, the optimal power allocation problem is solved in two steps. By employing the Lagrangian multiplier method with Karush-Kuhn-Tucker optimality conditions, the optimal power allocation is calculated for each subchannel. In addition, then, an inter-cluster dynamic programming model is further developed to achieve the overall maximum energy efficiency. The theoretical analysis and simulations show that the proposed schemes achieve a significant energy efficiency gain compared with existing methods.
引用
收藏
页码:1 / 19
页数:19
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