In recent years, energy harvesting has taken a considerable attention in wireless communication research. Nonetheless, the stochastic nature of renewable energy sources has become one of the research problems, and energy storage has been proposed as a solution to deal with it. Initially, researchers regarded a perfect battery model without energy losses during storage because of its simplicity and compatibility in wireless communication analysis. However, a battery model that reflects practical concerns should include energy losses. In this paper, we consider an energy harvesting wireless communication model with a battery that has energy losses during charging and discharging. We consider energy underflows (i.e., the energy level falls below a certain threshold in a battery) as the energy management concern, and characterize the energy underflow probability and provide a simple exponential formulation by employing the large deviation principle and queueing theory. Specifically, we benefit from the similarity between the battery and data buffer models. We further coin the available space decay rate at a battery as a parameter to indicate the energy consumption performance. We further outline an approach to set the energy demand policy to meet the energy management requirements that rule the energy underflow probability as a constraint. We finally substantiate our analytical findings with numerical demonstrations, and compare the transmission performance levels of a transmission system with a battery that has energy losses and a transmission system that consumes the energy as soon as it is harvested.
翻译:近年来,能源采集在无线通信研究中引起了相当大的关注。然而,可再生能源的随机性已成为研究问题之一,能源储存被提出来作为解决这一问题的解决方案。最初,研究人员认为在储存过程中没有能源损失的完美电池模型是因为它在无线通信分析中简单和兼容性而没有能源损失。然而,一个反映实际关注的电池模型应该包括能源损失。在本文件中,我们考虑一种能源采集无线通信模型,其电池在充电和放电过程中有能源损失。我们认为能源下流(即能源水平在电池中低于某一阈值)是能源管理问题,并用大量偏离原则和排队理论来说明能源流量的概率和提供简单的指数性配方。具体地说,我们受益于电池和数据缓冲模型之间的相似性。我们进一步将电池可用空间衰减率作为参数,以表明能源消耗绩效。我们进一步概述了一种方法来制定能源需求政策,以达到能源流量概率规则的能源管理要求,作为制约。我们最后用数字演示来证实我们的分析结论是能源流量概率的概率,并通过大量能源传输系统来比较能源损失。