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arXiv 1606.01416cs.ITcs.SYeess.SYmath.IT
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无线传输中带有能量采集与存储的在线功率控制优化

Online Power Control Optimization for Wireless Transmission with Energy Harvesting and Storage

Department of Electrical, Computer and Software Engineering, University of Ontario Institute of Technology(安大略理工大学电气、计算机与软件工程学院)

Fatemeh Amirnavaei, Min Dong

AI总结:

本文研究了在具有能量采集和存储设备的衰落信道中无线传输的在线功率控制优化问题,提出了一种基于Lyapunov优化的三阶段闭式解,通过电池能量控制实现战略性能源节约,并基于衰落条件进行机会性传输,从而提高长期时间平均传输速率。

摘要:

我们考虑由能量采集和存储设备供电的无线传输过衰落信道。假设电池存储容量有限,我们设计了一种在线功率控制策略,旨在在能量采集的电池操作约束下最大化长期时间平均传输速率。我们首先建立了随机优化问题,然后发展了将此问题转换的技术,并运用Lyapunov优化技术来设计在线功率控制方案。特别是,我们提出了一种处理无界信道衰落的方法,这种方法无法直接由Lyapunov框架处理。我们提出的算法仅根据电池的当前能量状态和信道衰落条件确定传输功率,而不需要任何关于能量到达统计和衰落信道的统计信息。我们的在线功率控制方案是依赖于电池能量水平的三阶段闭式解。它不仅通过电池能量控制实现了战略性的能源节约,还揭示了基于衰落条件的机会性传输方式,这两种方法都提高了长期时间平均传输速率。我们进一步对所提出算法的性能界限进行了表征,以一般衰落分布下的最优解。仿真结果展示了我们的所提出的在线算法在替代在线方法上的显著性能提升。

英文摘要:

We consider wireless transmission over fading channel powered by energy harvesting and storage devices. Assuming a finite battery storage capacity, we design an online power control strategy aiming at maximizing the long-term time-averaged transmission rate under battery operational constraints for energy harvesting. We first formulate the stochastic optimization problem, and then develop techniques to transform this problem and employ techniques from Lyapunov optimization to design the online power control solution. In particular, we propose an approach to handle unbounded channel fade which cannot by directly dealt with by Lyapunov framework. Our proposed algorithm determines the transmission power based only on the current energy state of the battery and channel fade conditions,without requiring any knowledge of the statistics of energy arrivals and fading channels. Our online power control solution is a three-stage closed-form solution depending on the battery energy level. It not only provides strategic energy conservation through the battery energy control, but also reveals an opportunistic transmission style based on fading condition, both of which improve the long-term time-averaged transmission rate. We further characterize the performance bound of our proposed algorithm to the optimal solution with a general fading distribution. Simulation results demonstrate a significant performance gain of our proposed online algorithm over alternative online approaches.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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