TDMA in Adaptive Resonant Beam Charging for IoT Devices

Xiong, Mingliang; Liu, Mingqing; Zhang, Qingqing; Liu, Qingwen; Wu, Jun; Xia, Pengfei

doi:10.1109/jiot.2018.2863232

Cited by 20 publications

(8 citation statements)

References 25 publications

(33 reference statements)

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“…23,24 Each subtask can select one edge server for computing. Assume that the bandwidth allocation between users is frequency division multiplexing; 25 that is, the communication between users does not interfere with each other. The goal of the user is to minimize the cost, and the goal of the edge server is to minimize the loss of benefits.…”

Section: Multi-user Multi-operator Bi-level Optimization Modelmentioning

confidence: 99%

A multi-user multi-operator computing pricing method for Internet of things based on bi-level optimization

Jiang

Wang

et al. 2020

International Journal of Distributed Sensor Networks

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The Internet of mobile things is a promising paradigm that generates, stores, and processes amount of real-time data to render rich services for mobile users. Along with the increase of mobile devices in the field of Internet of things, more and more intelligent applications, such as face recognition and virtual reality, have emerged. These applications typically consume large amounts of computing and energy resources. However, due to the physical size limitations of Internet of things terminals, their computing capacity and power are limited, where users’ needs for application processing delay and power consumption cannot be met. Therefore, the concept of edge cloud computing has been proposed, which enhances the computing capacity of Internet of things terminals by offloading user tasks to edge servers for computation. When there are multiple operators, it is important to understand how users choose an operator to perform computation and how operators can reasonably price the computing capacity to meet their own interests. Therefore, we study the computation pricing and user decision-making problems of Internet of things under multi-user and multi-operator scenarios. The problem is divided into three phases and modeled as a two-level optimization problem. While an operator’s goal is to minimize the loss of his interests, the user’s goal is to minimize the computation cost (energy consumption and price). First, since the lower-level user decision-making problem is an integer linear programming problem, we transform it into an equivalent continuous linear programming problem by relaxation. Second, we transform the bi-level optimization problem into an equivalent single-level optimization problem by substituting the lower problem’s Karush–Kuhn–Tucker conditions into an upper problem. Finally, we use a spatial branch and bound algorithm to solve the problem. Experimental results show that the proposed algorithm can effectively maintain the benefits of both operators and users in the field of Internet of things.

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Section: Multi-user Multi-operator Bi-level Optimization Modelmentioning

confidence: 99%

A multi-user multi-operator computing pricing method for Internet of things based on bi-level optimization

Jiang

Wang

et al. 2020

International Journal of Distributed Sensor Networks

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“…Based on RBC, for better charging services, wireless power scheduling algorithm in terms of battery charging profile for fairly keeping all devices working as long as possible is proposed [8]. Moreover, the scheduling algorithm for earning maximization with quality of charging service guarantee [9], and the TDMA-based WPT scheduling algorithm for efficient WPT in ARBC [10] are put forth. These efforts are to drive the progress and implementation of wireless charging services.…”

Section: B Recent Progress In Rbc Researchmentioning

confidence: 99%

Mobile Power Network for Ultimate Mobility without Battery Life Anxiety

Liu

Xiong

Deng

et al. 2018

Preprint

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Similar to the evolution from the wired Internet to mobile Internet (MI), the growing demand for power delivery anywhere and anytime appeals for power grid transformation from wired to mobile domain. We propose here the next generation of power delivery network mobile power network (MPN) for wireless power transfer within a mobile range from several meters to tens of meters. At first, we present the MPN's concept evolution and application scenarios.Then, we introduce the MPN's supporting technology, namely resonant beam charging (RBC). As a long-range wireless power transfer (WPT) method, RBC can safely deliver multi-Watt power to multiple devices concurrently.Meanwhile, the recent progress in RBC research has been summarized. Next, we specify the MPN's architecture to provide the wide-area WPT coverage. Finally, we discuss the MPN's features and challenges. MPN can enable the ultimate mobility by cutting the final cord of mobile devices, realizing the "last-mile" mobile power delivery.

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“…verified that the energy transfer of the RBS using solid-state gain medium can achieve 2W power transfer over 2.6m in experiment [11]. To support multiuser access into the RBS, Xiong et al proposed a time-division multiple access (TDMA) RBS design for wireless power transfer [18]. Xiong et al also proposed the RBS communication design and presented the analytical model in [19].…”

Section: Introductionmentioning

confidence: 97%

High-Efficiency Resonant Beam Charging and Communication

Bai¹,

Liu²,

Wang³

et al. 2021

Preprint

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Simultaneous wireless information and power transfer (SWIPT) has been envisioned as an enabling technology for future 6G by providing high-efficiency power transfer and high-rate data transmissions concurrently. In this paper, we propose a resonant beam charging and communication (RBCC) system utilizing the telescope internal modulator (TIM) and the semiconductor gain medium. TIM can concentrate the diverged beam into a small-size gain module, thus the propagation loss is reduced and the transmission efficiency is enhanced. Since the semiconductor gain medium has better energy absorption capacity compared with the traditional solid-state one, the overall energy conversion efficiency can be improved. We establish an analytical model of this RBCC system for SWIPT and evaluate its stability, output energy, and spectral efficiency. Numerical analysis shows that the proposed RBCC system can realize stable SWIPT over 10 meters, whose energy conversion efficiency is increased by 14 times compared with the traditional system using the solid-state gain medium without TIM, and the spectrum efficiency can be above 15 bit/s/Hz.

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TDMA in Adaptive Resonant Beam Charging for IoT Devices

Cited by 20 publications

References 25 publications

A multi-user multi-operator computing pricing method for Internet of things based on bi-level optimization

A multi-user multi-operator computing pricing method for Internet of things based on bi-level optimization

Mobile Power Network for Ultimate Mobility without Battery Life Anxiety

High-Efficiency Resonant Beam Charging and Communication

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