Energy Efficient Online Power Allocation for Two Users With Energy Harvesting

Ashraf, Mateen; Jung, Jaehoon; Shin, Hun Min; Lee, Inkyu

doi:10.1109/lsp.2018.2878947

Cited by 8 publications

(6 citation statements)

References 25 publications

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“…Amirnavaei et al 32 have designed an online energy control policy by Lyapunov framework to maximize the long‐term average wireless transmission rate under a finite battery storage limitation with energy harvesting. An online power allocation method for energy harvesting systems under practical battery constraints is presented to maximize energy efficiency by utilizing the Lyapunov technique 33 . Yu et al 34 have developed a learning aided energy control strategy aiming at utility optimization for energy harvesting devices considering out‐of‐date status information and unknown status distribution information.…”

Section: Related Workmentioning

confidence: 99%

Energy allocation for activity recognition in wearable devices with kinetic energy harvesting

Ling

Meng²,

Tian

et al. 2021

Softw Pract Exp

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Harvesting kinetic energy from body movement is regarded as a promising rechargeable energy source for wearable devices with low‐power. Energy allocation is essential for motion‐based rechargeable devices since the great variability of energy gained from movement. Based on the realistic characteristics of an ultra‐low‐power wearable devices and our measurement observations, we propose the optimization framework allocating energy to maximize the average accuracy of human activity recognition and provide an offline and online algorithm, respectively. We evaluate the proposed energy allocation approach with real‐world human activity and kinetic energy harvesting datasets. Experimental results validate that our proposed energy allocation approach can maximize the energy allocation utility and improve energy efficiency of wearable devices.

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Section: Related Workmentioning

confidence: 99%

Energy allocation for activity recognition in wearable devices with kinetic energy harvesting

Ling

Meng²,

Tian

et al. 2021

Softw Pract Exp

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“…The optimization problem in P1 can be relaxed by replacing the dynamics in (1) with the long-term time-average constraint (12) and by removing (6b). After doing these steps, we have the relaxed optimization problem of P1 as follows…”

Section: A Non-orthogonal Multiple Access Without Individual User Rat...mentioning

confidence: 99%

“…However, a single user scenario was considered in these works. More recently, an energy efficiency maximization problem was considered in [12] for only two users case. In their work, the total bandwidth and power is equally split between the two users and therefore the possibility of inter-user interference was not considered.…”

Section: Introductionmentioning

confidence: 99%

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Online Power Allocation at Energy Harvesting Transmitter for Multiple Receivers with and without Individual Rate Constraints for OMA and NOMA Transmissions

Ashraf¹,

Wang²,

Vandendorpe³

2019

Preprint

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In this paper, we propose an online power allocation scheme to maximize the time averaged sum rate for multiple downlink receivers with energy harvesting transmitter. The transmitter employs non-orthogonal multiple access (NOMA) and/or orthogonal multiple access (OMA) to transmit data to multiple users. Additionally, we consider the scenario where each individual user has a quality of service constraint on its required instantaneous rate. The decisions of total transmit power and power allocation for different users in a given time slot are obtained with the help of Lyapunov optimization technique. The proposed schemes do not require any statistical information of the channel states and the harvested energy. The proposed power allocation schemes entail in small complexity based power allocation decisions. Therefore, the proposed schemes can provide solutions in real time and are more suited for online power allocation problems where the system state parameters (e.g. channel state, harvested energy etc) change quickly. The performances of the proposed schemes are demonstrated with the help of simulation results.

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“…As a result, the power control problem of a EH based transmitter, which harvests energy from ambient environment and transmits information to remote wireless receivers with harvested energy is a big challenge [6]. The unknown wireless channel and intermittent nature of ambient environmental energy lead to the challenges of ensuring node continuity and maximizing communication throughput [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Online Power Control and Optimization for Energy Harvesting Communication System Based on State of Charge

Guo

Zhang

2021

Wireless Pers Commun

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In this paper, the online power control problem for energy harvesting wireless communication system with a finite storage capacity battery is addressed, where the channel state and energy harvesting rate are both unknown. A low complexity algorithm based online convex optimization is proposed to guarantee energy availability of energy harvesting node and maximize average long-term throughput. The proposed algorithm restricts maximum transmission power with the information of state of charge, and allocates transmission power based on historical information. In addition, energy availability constraint is given by rigorous theoretical analysis to guarantee the optimization of average long-term throughput. Simulations have been conducted to demonstrate the effectiveness of the algorithm without considering probability distribution of energy arrival or channel coefficients. The proposed algorithm outperforms counterparts in different energy harvested rates.

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Energy Efficient Online Power Allocation for Two Users With Energy Harvesting

Cited by 8 publications

References 25 publications

Energy allocation for activity recognition in wearable devices with kinetic energy harvesting

Energy allocation for activity recognition in wearable devices with kinetic energy harvesting

Online Power Allocation at Energy Harvesting Transmitter for Multiple Receivers with and without Individual Rate Constraints for OMA and NOMA Transmissions

Online Power Control and Optimization for Energy Harvesting Communication System Based on State of Charge

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