Transmission with Energy Harvesting Nodes in Fading Wireless Channels: Optimal Policies
Transmission with Energy Harvesting Nodes in Fading Wireless Channels: Optimal Policies
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DOI：
10.1109/jsac.2011.110921
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发表时间：
2011-09-01
影响因子：
16.4
通讯作者：
Yener, Aylin
中科院分区：
文献类型：
--
作者：
Ozel, Omur;Tutuncuoglu, Kaya;Yener, Aylin
由可充电节点组成的无线系统具有明显延长的寿命，并且具有可持续性。这些系统的一个独特特征是，节点可以在进行通信的整个过程中收获能量。因此，节点的传输策略需要适应这些收获的能量到达。在本文中，我们考虑使用电池容量有限的能量收集发射器对点对点数据传输进行优化，该发射器在无线褪色通道中进行通信。我们考虑两个目标：通过截止日期最大化吞吐量，并最大程度地减少通信会话的传输完成时间。我们通过控制受储能容量和因果关系约束的发射功率的时间顺序来优化这些目标。首先，我们研究最佳的离线政策。我们介绍了一种定向水填充算法，该算法对必要的最佳条件提供了简单明了的解释。我们显示了针对吞吐量最大化问题的自适应定向填充算法的最佳性。我们通过利用其与其吞吐量最大化对应物的等效性来解决传输完成时间最小化问题。接下来，我们考虑在线政策。我们使用随机动态编程来解决最佳的在线政策，该政策最大限度地提高了通过因果渠道状态反馈，在随机褪色和能量到达过程中截止日期的平均数量。我们还提出了具有降低复杂性的近乎最佳策略，并在各种不同的配置下进行数值研究以及离线和在线最佳策略的表现。
Wireless systems comprised of rechargeable nodes have a significantly prolonged lifetime and are sustainable. A distinct characteristic of these systems is the fact that the nodes can harvest energy throughout the duration in which communication takes place. As such, transmission policies of the nodes need to adapt to these harvested energy arrivals. In this paper, we consider optimization of point-to-point data transmission with an energy harvesting transmitter which has a limited battery capacity, communicating in a wireless fading channel. We consider two objectives: maximizing the throughput by a deadline, and minimizing the transmission completion time of the communication session. We optimize these objectives by controlling the time sequence of transmit powers subject to energy storage capacity and causality constraints. We, first, study optimal offline policies. We introduce a directional water-filling algorithm which provides a simple and concise interpretation of the necessary optimality conditions. We show the optimality of an adaptive directional water-filling algorithm for the throughput maximization problem. We solve the transmission completion time minimization problem by utilizing its equivalence to its throughput maximization counterpart. Next, we consider online policies. We use stochastic dynamic programming to solve for the optimal online policy that maximizes the average number of bits delivered by a deadline under stochastic fading and energy arrival processes with causal channel state feedback. We also propose near-optimal policies with reduced complexity, and numerically study their performances along with the performances of the offline and online optimal policies under various different configurations.