机构地区:[1]National Mobile Communications Research Laboratory, Southeast University
出 处:《Science China(Information Sciences)》2019年第4期136-152,共17页中国科学(信息科学)(英文版)
基 金:supported by National Major Project (Grant No. 2017ZX03001002-004);National Natural Science Foundation Project (Grant No. 61521061);333 Program of Jiangsu (Grant No. BRA2017366)
摘 要:Ultra-dense network (UDN) has been recognized as a promising technology for 5G. Although turning off low-load base stations (BSs) can improve energy efficiency, it may cause degradation of delay performance. This makes energy-delay tradeoff (EDT) an important topic. In this paper, a theoretical framework for EDT, in wireless-backhauling UDN, is developed. First, we investigate association probabilities of UEs and transmission probabilities of BSs. Expressions for energy consumption and network packet delay are obtained and the impact that BS sleeping ratio has on energy consumption and packet delay are analyzed.Then, we formulate the EDT problem as a cost minimization problem to select the optimal set of sleeping small cells. To solve the EDT optimization problem, a locally optimal sleeping ratio for EDT is obtained using the dynamic gradient iteration algorithm and we prove that it can converge to the global optimal sleeping ratio. Then, queue-aware and channel-queue-aware sleeping strategies are proposed to find the optimal set of sleeping small cells according to the optimal sleeping ratio. We then see that the simulation and numerical results confirm the effectiveness of the proposed sleeping schemes.Ultra-dense network (UDN) has been recognized as a promising technology for 5G. Although turning off low-load base stations (BSs) can improve energy efficiency, it may cause degradation of delay performance. This makes energy-delay tradeoff (EDT) an important topic. In this paper, a theoretical framework for EDT, in wireless-backhauling UDN, is developed. First, we investigate association probabilities of UEs and transmission probabilities of BSs. Expressions for energy consumption and network packet delay are obtained and the impact that BS sleeping ratio has on energy consumption and packet delay are analyzed.Then, we formulate the EDT problem as a cost minimization problem to select the optimal set of sleeping small cells. To solve the EDT optimization problem, a locally optimal sleeping ratio for EDT is obtained using the dynamic gradient iteration algorithm and we prove that it can converge to the global optimal sleeping ratio. Then, queue-aware and channel-queue-aware sleeping strategies are proposed to find the optimal set of sleeping small cells according to the optimal sleeping ratio. We then see that the simulation and numerical results confirm the effectiveness of the proposed sleeping schemes.
关 键 词:ultra-dense networks SLEEPING ratio SLEEPING STRATEGY WIRELESS BACKHAUL energy-delay TRADEOFF
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