Adaptive wireless sensor networks powered by hybrid energy harvesting for environmental monitoring

Philipp, François; Zhao, Peng; Samman, Faizal Arya; Glesner, Manfred; Dassanayake, K. B.; Maheswararajah, Suhinthan; Halgamuge, Saman K.

doi:10.1109/iciafs.2012.6419918

Cited by 9 publications

(6 citation statements)

References 13 publications

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“…They can act as information collectors to sample the received signals and store them for future decoding by other energy unlimited and powerful computational devices 6. In fact, nowadays many sensors are equipped with hybrid energy harvesters for harvesting energy from different energy sources such as solar and thermalenergy[38],[39]. Thus, the harvested energy from the radio frequency may be used as a supplement for supporting the energy consumption of the secondary receivers.…”

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confidence: 99%

Multiobjective Resource Allocation for Secure Communication in Cognitive Radio Networks With Wireless Information and Power Transfer

Lo²,

Schober

2016

IEEE Trans. Veh. Technol.

234

201

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In this paper, we study resource allocation for multiuser multiple-input single-output (MISO) secondary communication systems with multiple system design objectives. We consider cognitive radio (CR) networks where the secondary receivers are able to harvest energy from the radio frequency when they are idle. The secondary system provides simultaneous wireless power and secure information transfer to the secondary receivers. We propose a multi-objective optimization framework for the design of a Pareto optimal resource allocation algorithm based on the weighted Tchebycheff approach. In particular, the algorithm design incorporates three important system design objectives: total transmit power minimization, energy harvesting efficiency maximization, and interference power leakage-to-transmit power ratio minimization. The proposed framework takes into account a quality of service (QoS) requirement regarding communication secrecy in the secondary system and the imperfection of the channel state information (CSI) of potential eavesdroppers (idle secondary receivers and primary receivers) at the secondary transmitter. The proposed framework includes total harvested power maximization and interference power leakage minimization as special cases. The adopted multi-objective optimization problem is non-convex and is recast as a convex optimization problem via semidefinite programming (SDP) relaxation. It is shown that the global optimal solution of the original problem can be constructed by exploiting both the primal and the dual optimal solutions of the SDP relaxed problem. Besides, two suboptimal resource allocation schemes for the case when the solution of the dual problem is unavailable for constructing the optimal solution are proposed. Numerical results not only demonstrate the closeto-optimal performance of the proposed suboptimal schemes, but also unveil an interesting trade-off between the considered conflicting system design objectives.Index Terms-Physical (PHY) layer security, cognitive radio (CR), wireless information and power transfer, robust beamforming.

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mentioning

confidence: 99%

Multiobjective Resource Allocation for Secure Communication in Cognitive Radio Networks With Wireless Information and Power Transfer

Lo²,

Schober

2016

IEEE Trans. Veh. Technol.

234

201

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“…is used for maintaining the routine operations in the receiver and is independent of the amount of harvested power. We note that in practice the receivers may be powered by more than one energy source and the harvested energy may be used as a supplement for supporting the energy consumption 3 of the receivers [17].…”

Section: B Hybrid Information and Energy Harvesting Receivermentioning

confidence: 99%

Wireless Information and Power Transfer: Energy Efficiency Optimization in OFDMA Systems

Schober

2013

IEEE Trans. Wireless Commun.

482

423

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Abstract-This paper considers orthogonal frequency division multiple access (OFDMA) systems with simultaneous wireless information and power transfer. We study the resource allocation algorithm design for maximization of the energy efficiency of data transmission (bits/Joule delivered to the receivers). In particular, we focus on power splitting hybrid receivers which are able to split the received signals into two power streams for concurrent information decoding and energy harvesting. Two scenarios are investigated considering different power splitting abilities of the receivers. In the first scenario, we assume receivers which can split the received power into a continuous set of power streams with arbitrary power splitting ratios. In the second scenario, we examine receivers which can split the received power only into a discrete set of power streams with fixed power splitting ratios. For both scenarios, we formulate the corresponding algorithm design as a non-convex optimization problem which takes into account the circuit power consumption, the minimum data rate requirements of delay constrained services, the minimum required system data rate, and the minimum amount of power that has to be delivered to the receivers. By exploiting fractional programming and dual decomposition, suboptimal iterative resource allocation algorithms are developed to solve the nonconvex problems. Simulation results illustrate that the proposed iterative resource allocation algorithms approach the optimal solution within a small number of iterations and unveil the tradeoff between energy efficiency, system capacity, and wireless power transfer: (1) wireless power transfer enhances the system energy efficiency by harvesting energy in the radio frequency, especially in the interference limited regime; (2) the presence of multiple receivers is beneficial for the system capacity, but not necessarily for the system energy efficiency.Index Terms-Energy efficiency, green communications, wireless information and power transfer, non-convex optimization.

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“…So energy must be harvested from other sources when sunlight is not available. In [19], the thermoelectric power generation was used in addition to solar panels making it hybrid. Accumulated heat can be converted to charge the sensor node battery in electrical energy enough at the same time.…”

Section: Solar Energy or Light Energymentioning

confidence: 99%

“…The application of ambient vibration research has been given by Anton and Sodano [24]. Enough energy at the resonance frequency of the vibrating body can be accumulated to power these nodes; it was used on animals [19]. Some simple directions of vibration energy harvesting are given.…”

Section: Vibration Energymentioning

confidence: 99%

A Survey on Energy Harvesting and Integrated Data Sharing in Wireless Body Area Networks

Shu

Guizani

et al. 2015

International Journal of Distributed Sensor Networks

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Wireless body area networks (WBANs) are important branches of wireless sensor networks (WSNs). They promise unobtrusive ambulatory health monitoring for real-time updates of patients’ medical records that have aroused extensive attention in various fields. In recent years, one can find a lot of researches related to WBANs that have appeared in these literatures. But there are still many key issues that need to be further investigated. This paper briefly introduces the architecture and features of WBANs. In this attempt, we focus mostly on energy acquisition, data integration and data sharing, and collaboration of WBANs, from the viewpoint of energy harvesting development, the social network and smartphone application in WBANs, and the integration of WBANs and cloud system networks computing to analyze related issues of WBANs. Finally, we put forward concluding remarks with several future research directions.

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Adaptive wireless sensor networks powered by hybrid energy harvesting for environmental monitoring

Cited by 9 publications

References 13 publications

Multiobjective Resource Allocation for Secure Communication in Cognitive Radio Networks With Wireless Information and Power Transfer

Multiobjective Resource Allocation for Secure Communication in Cognitive Radio Networks With Wireless Information and Power Transfer

Wireless Information and Power Transfer: Energy Efficiency Optimization in OFDMA Systems

A Survey on Energy Harvesting and Integrated Data Sharing in Wireless Body Area Networks

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