Frameworks for Energy Efficiency Maximization in HetNets With Millimeter Wave Backhaul Links

被引:6
作者
Aboagye, Sylvester [1 ]
Ibrahim, Ahmed [1 ]
Ngatched, Telex M. N. [1 ]
机构
[1] Mem Univ Newfoundland, Fac Engn & Appl Sci, St John, NF A1C 5S7, Canada
来源
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING | 2020年 / 4卷 / 01期
基金
加拿大自然科学与工程研究理事会;
关键词
User association; flow control; power control; generalized assignment problem; multiplier adjustment method; subgradient; Lagrangian multipliers; RESOURCE-ALLOCATION; WIRELESS BACKHAUL; BANDWIDTH ALLOCATION; CELLULAR NETWORKS; USER ASSOCIATION; SMALL-CELLS; POWER; TRANSMISSION;
D O I
10.1109/TGCN.2019.2949288
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Heterogeneous networks (HetNets) and millimeter wave (mmWave) communications have been recognized as two of the most promising techniques for future cellular networks. HetNets possess the ability to significantly increase network capacity and coverage, while the mmWave bands have an abundant spectrum to support gigabit-per-second data transmission for backhauling. Due to the extreme pathloss and the unreliable transmission of mmWave signals over longer distances, multi-hop mmWave transmissions have been identified as a backhaul (BH) solution in HetNets. On the other hand, energy efficiency (EE) has been identified as a prime design factor for cellular networks because of their rising energy costs. In this paper, two optimization frameworks for maximizing the EE of HetNets with multi-hop mmWave BH links are explored. The first framework, referred to as joint EE, power, and flow control (JEEPF), considers enforcing a strict throughput requirement on all user equipment (UEs) and maximizing the network EE via the joint optimization of power and BH flows. The second framework, referred to as joint EE, power, flow, and throughput (JEEPFT), allows an acceptable range of throughput requirements for each UE and maximizes the network EE via the joint optimization of power, BH flows, and UEs' achievable throughputs. It is observed that this little change (i.e., strict vs. an acceptable range of throughput requirements) causes a drastic difference in the formulations of both problems. The JEEPF simplifies to power minimization problem (which is convex), while the JEEPFT is a ratio of throughput to power (which is fractional and non-convex). Two solution techniques that obtain the optimal solution are proposed for the JEEPFT optimization framework. Simulation results are used to demonstrate the superiority of the JEEPFT framework over the JEEPF and other simple benchmark schemes. The computational complexity of the JEEPFT solution techniques is discussed.
引用
收藏
页码:83 / 94
页数:12
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