Resource allocation for energy efficient user association in user-centric ultra-dense networks integrating NOMA and beamforming

被引:11
|
作者
Zhang, Long [1 ]
Zhang, Guobin [2 ]
Zhao, Xiaofang [2 ]
Li, Yali [2 ]
Huang, Chuntian [2 ]
Sun, Enchang [3 ,4 ]
Huang, Wei [5 ]
机构
[1] Hebei Univ Engn, Sch Informat & Elect Engn, Handan 056038, Peoples R China
[2] Dongguan Univ Technol, Sch Elect Engn & Intelligentizat, Dongguan 523808, Peoples R China
[3] Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Beijing 100124, Peoples R China
[4] Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
[5] China Elect Power Res Inst, Inst Power & Energy Efficiency, Beijing 100192, Peoples R China
基金
中国国家自然科学基金;
关键词
Ultra-dense network (UDN); Resource allocation; User association; Non-orthogonal multiple access (NOMA); Beamforming; User-centric networking; Energy efficiency; POWER ALLOCATION; OPTIMIZATION; CHALLENGES; SYSTEMS; DESIGN;
D O I
10.1016/j.aeue.2020.153270
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
A coupling of wireless access via non-orthogonal multiple access and wireless backhaul via beamforming is a promising way for downlink user-centric ultra-dense networks (UDNs) to improve system performance. However, ultra-dense deployment of radio access points in macrocell and user-centric view of network design in UDNs raise important concerns about resource allocation and user association, among which notably is energy efficiency (EE) balance. To overcome this challenge, we develop a framework to investigate the resource allocation problem for energy efficient user association in such a scenario. The joint optimization framework aiming at the system EE maximization is formulated as a large-scale non-convex mixed-integer nonlinear programming problem, which is NP-hard to solve directly with lower complexity. Alternatively, taking advantages of sum-of-ratios decoupling and successive convex approximation methods, we transform the original problem into a series of convex optimization subproblems. Then we solve each subproblem through Lagrangian dual decomposition, and design an iterative algorithm in a distributed way that realizes the joint optimization of power allocation, sub-channel assignment, and user association simultaneously. Simulation results demonstrate the effectiveness and practicality of our proposed framework, which achieves the rapid convergence speed and ensures a beneficial improvement of system-wide EE. (C) 2020 Elsevier GmbH. All rights reserved.
引用
收藏
页数:19
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