Power-Delay Tradeoff With Predictive Scheduling in Integrated Cellular and Wi-Fi Networks
Power-Delay Tradeoff With Predictive Scheduling in Integrated Cellular and Wi-Fi Networks
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DOI：
10.1109/jsac.2016.2544639
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发表时间：
2015-12
影响因子：
16.4
通讯作者：
Haoran Yu;M. H. Cheung;Longbo Huang-;Jianwei Huang
中科院分区：
文献类型：
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作者：
Haoran Yu;M. H. Cheung;Longbo Huang-;Jianwei Huang
全球移动的业务的爆炸性增长导致通信网络中的能量消耗的快速增长。在本文中，我们专注于在蜂窝和Wi-Fi网络中的网络选择，子信道和功率分配的能量感知设计，同时考虑到移动的用户的业务延迟。基于双时间尺度李雅普诺夫优化技术，我们首先设计了一种在线能量感知网络选择和资源分配（ENSRA）算法，该算法产生的功耗在最优值的O（1/V）范围内，并且对于任何正控制参数V都保证O（V）的业务延迟。和流量需求，进一步发展了一种新的预测李亚普诺夫优化技术来利用预测信息，并提出了一种预测能量感知网络选择和资源分配（P-ENSRA）算法。我们从理论上描述了P-ENSRA的功率延迟权衡性能界限。为了降低计算复杂度，本文提出了一种贪婪预测能量感知网络选择和资源分配（GP-ENSRA）算法，该算法通过迭代近似求解P-ENSRA中的问题。数值结果表明，GP-ENSRA在大时延范围内显著改善了ENSRA的功率时延性能。在各种系统参数下，GP-ENSRA在相同功耗下比ENSRA减少了20-30%的业务延迟。
The explosive growth of global mobile traffic has led to rapid growth in the energy consumption in communication networks. In this paper, we focus on the energy-aware design of the network selection, subchannel, and power allocation in cellular and Wi-Fi networks, while taking into account the traffic delay of mobile users. Based on the two-timescale Lyapunov optimization technique, we first design an online Energy-Aware Network Selection and Resource Allocation (ENSRA) algorithm, which yields a power consumption within O(1/V)bound of the optimal value, and guarantees an O(V) traffic delay for any positive control parameter V. Motivated by the recent advancement in the accurate estimation and prediction of user mobility, channel conditions, and traffic demands, we further develop a novel predictive Lyapunov optimization technique to utilize the predictive information, and propose a Predictive Energy-Aware Network Selection and Resource Allocation (P-ENSRA) algorithm. We characterize the performance bounds of P-ENSRA in terms of the power-delay tradeoff theoretically. To reduce the computational complexity, we finally propose a Greedy Predictive Energy-Aware Network Selection and Resource Allocation (GP-ENSRA) algorithm, where the operator solves the problem in P-ENSRA approximately and iteratively. Numerical results show that GP-ENSRA significantly improves the power-delay performance over ENSRA in the large delay regime. For a wide range of system parameters, GP-ENSRA reduces the traffic delay over ENSRA by 20-30% under the same power consumption.