Efficient multichannel energy harvesting with dedicated energy transmitters in CR-IoT networks

IF 4.4 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Computer Networks Pub Date : 2024-10-01 DOI:10.1016/j.comnet.2024.110834

Hisham M. Almasaeid

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Abstract

Radio Frequency (RF) energy harvesting is strongly believed to be a sustainable solution to the power depletion problem in battery powered IoT devices. In addition to harvesting energy from ambient RF signals, the use of dedicated energy transmitters (ETs) that transmit energy to nearby IoT devices via RF signals has recently been proposed. In this paper, we study the problem of designing an energy harvesting policy for a group of cognitive radio-enabled IoT (CR-IoT) devices served by a number of ETs to maximize the minimum of their charging rates. With the help of cognitive radios, a CR-IoT node is capable of changing its frequency channel of operation allowing for multi-channel energy harvesting. Frequency channels are assumed to be opportunistically accessible depending on the activity of wireless users that are licensed to use those channels. The problem entails the design of the ET’s transmission policy (to what CR-IoT device, and over what channel) and the design of an ambient harvesting policy for every CR-IoT device (when it is not served by ETs). The problem is formulated as a mixed integer linear program (MILP). The objective is to maximize a lower bound on the total harvested energy in a given time frame per CR-IoT node. This optimization is subject to scheduling, total energy budget, and maximum transmit power constraints. Given the intractability of MILP formulations, a sub-optimal algorithm is proposed. Extensive experimentation is carried out to assess the effectiveness of the proposed sub-optimal algorithm by comparing it to the MILP’s solution obtained using IBM CPLEX solver with a limit on the execution time. We also combine our sub-optimal algorithm withe the CPLEX solver to produce a new two-stages algorithm that improves the original one by around 47%. Finally, we investigate the effect of multiple parameters including number of ETs, number of channels, and channel availability probability on the minimum charging rate.

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在 CR-IoT 网络中利用专用能量发射器实现高效多通道能量采集

射频（RF）能量采集被认为是解决电池供电的物联网设备电能耗尽问题的一种可持续解决方案。除了从环境射频信号中采集能量外，最近还有人提出使用专用能量发射器（ET），通过射频信号向附近的物联网设备发射能量。在本文中，我们研究了为一组由多个 ET 提供服务的认知无线电物联网（CR-IoT）设备设计能量收集策略的问题，以最大限度地降低其充电率。在认知无线电的帮助下，CR-IoT 节点能够改变其工作频率信道，从而实现多信道能量收集。假定频率信道可根据获得使用许可的无线用户的活动情况伺机访问。该问题需要设计 ET 的传输策略（向哪些 CR-IoT 设备、通过哪些信道），以及为每个 CR-IoT 设备（在没有 ET 服务时）设计环境能量收集策略。该问题被表述为混合整数线性规划（MILP）。目标是在给定时间框架内最大化每个 CR-IoT 节点的总采集能量下限。这一优化受调度、总能量预算和最大发射功率约束。鉴于 MILP 公式的难解性，提出了一种次优算法。我们进行了广泛的实验，通过与使用 IBM CPLEX 求解器获得的 MILP 解法（执行时间有限制）进行比较，来评估所提出的次优算法的有效性。我们还将次优算法与 CPLEX 求解器相结合，产生了一种新的两阶段算法，该算法比原始算法提高了约 47%。最后，我们研究了 ET 数量、信道数量和信道可用性概率等多个参数对最小充电率的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computer Networks 工程技术-电信学

CiteScore

10.80

自引率

3.60%

发文量

434

审稿时长

8.6 months

期刊介绍： Computer Networks is an international, archival journal providing a publication vehicle for complete coverage of all topics of interest to those involved in the computer communications networking area. The audience includes researchers, managers and operators of networks as well as designers and implementors. The Editorial Board will consider any material for publication that is of interest to those groups.