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3697 KiB

Open AccessArticle

Wireless Monitoring of Induction Machine Rotor Physical Variables

by Jefferson Doolan Fernandes, Francisco Elvis Carvalho Souza, Glauco George Cipriano Maniçoba, Andrés Ortiz Salazar and José Alvaro De Paiva

Sensors 2017, 17(11), 2660; https://doi.org/10.3390/s17112660 - 18 Nov 2017

Cited by 8 | Viewed by 4783

Abstract

With the widespread use of electric machines, there is a growing need to extract information from the machines to improve their control systems and maintenance management. The present work shows the development of an embedded system to perform the monitoring of the rotor [...] Read more.

With the widespread use of electric machines, there is a growing need to extract information from the machines to improve their control systems and maintenance management. The present work shows the development of an embedded system to perform the monitoring of the rotor physical variables of a squirrel cage induction motor. The system is comprised of: a circuit to acquire desirable rotor variable(s) and value(s) that send it to the computer; a rectifier and power storage circuit that converts an alternating current in a continuous current but also stores energy for a certain amount of time to wait for the motor’s shutdown; and a magnetic generator that harvests energy from the rotating field to power the circuits mentioned above. The embedded system is set on the rotor of a 5 HP squirrel cage induction motor, making it difficult to power the system because it is rotating. This problem can be solved with the construction of a magnetic generator device to avoid the need of using batteries or collector rings and will send data to the computer using a wireless NRF24L01 module. For the proposed system, initial validation tests were made using a temperature sensor (DS18b20), as this variable is known as the most important when identifying the need for maintenance and control systems. Few tests have shown promising results that, with further improvements, can prove the feasibility of using sensors in the rotor. Full article

(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)

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972 KiB

Open AccessArticle

Wireless Energy Harvesting Two-Way Relay Networks with Hardware Impairments

by Chunling Peng, Fangwei Li and Huaping Liu

Sensors 2017, 17(11), 2604; https://doi.org/10.3390/s17112604 - 13 Nov 2017

Cited by 13 | Viewed by 4998

Abstract

This paper considers a wireless energy harvesting two-way relay (TWR) network where the relay has energy-harvesting abilities and the effects of practical hardware impairments are taken into consideration. In particular, power splitting (PS) receiver is adopted at relay to harvests the power it [...] Read more.

This paper considers a wireless energy harvesting two-way relay (TWR) network where the relay has energy-harvesting abilities and the effects of practical hardware impairments are taken into consideration. In particular, power splitting (PS) receiver is adopted at relay to harvests the power it needs for relaying the information between the source nodes from the signals transmitted by the source nodes, and hardware impairments is assumed suffered by each node. We analyze the effect of hardware impairments on both decode-and-forward (DF) relaying and amplify-and-forward (AF) relaying networks. By utilizing the obtained new expressions of signal-to-noise-plus-distortion ratios, the exact analytical expressions of the achievable sum rate and ergodic capacities for both DF and AF relaying protocols are derived. Additionally, the optimal power splitting (OPS) ratio that maximizes the instantaneous achievable sum rate is formulated and solved for both protocols. The performances of DF and AF protocols are evaluated via numerical results, which also show the effects of various network parameters on the system performance and on the OPS ratio design. Full article

(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)

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511 KiB

Open AccessArticle

Joint Power Charging and Routing in Wireless Rechargeable Sensor Networks

by Jie Jia, Jian Chen, Yansha Deng, Xingwei Wang and Abdol-Hamid Aghvami

Sensors 2017, 17(10), 2290; https://doi.org/10.3390/s17102290 - 9 Oct 2017

Cited by 22 | Viewed by 5503

Abstract

The development of wireless power transfer (WPT) technology has inspired the transition from traditional battery-based wireless sensor networks (WSNs) towards wireless rechargeable sensor networks (WRSNs). While extensive efforts have been made to improve charging efficiency, little has been done for routing optimization. In [...] Read more.

The development of wireless power transfer (WPT) technology has inspired the transition from traditional battery-based wireless sensor networks (WSNs) towards wireless rechargeable sensor networks (WRSNs). While extensive efforts have been made to improve charging efficiency, little has been done for routing optimization. In this work, we present a joint optimization model to maximize both charging efficiency and routing structure. By analyzing the structure of the optimization model, we first decompose the problem and propose a heuristic algorithm to find the optimal charging efficiency for the predefined routing tree. Furthermore, by coding the many-to-one communication topology as an individual, we further propose to apply a genetic algorithm (GA) for the joint optimization of both routing and charging. The genetic operations, including tree-based recombination and mutation, are proposed to obtain a fast convergence. Our simulation results show that the heuristic algorithm reduces the number of resident locations and the total moving distance. We also show that our proposed algorithm achieves a higher charging efficiency compared with existing algorithms. Full article

(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)

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13659 KiB

Open AccessArticle

ePave: A Self-Powered Wireless Sensor for Smart and Autonomous Pavement

by Jian Xiao, Xiang Zou and Wenyao Xu

Sensors 2017, 17(10), 2207; https://doi.org/10.3390/s17102207 - 26 Sep 2017

Cited by 33 | Viewed by 12394

Abstract

“Smart Pavement” is an emerging infrastructure for various on-road applications in transportation and road engineering. However, existing road monitoring solutions demand a certain periodic maintenance effort due to battery life limits in the sensor systems. To this end, we present an end-to-end self-powered [...] Read more.

“Smart Pavement” is an emerging infrastructure for various on-road applications in transportation and road engineering. However, existing road monitoring solutions demand a certain periodic maintenance effort due to battery life limits in the sensor systems. To this end, we present an end-to-end self-powered wireless sensor—ePave—to facilitate smart and autonomous pavements. The ePave system includes a self-power module, an ultra-low-power sensor system, a wireless transmission module and a built-in power management module. First, we performed an empirical study to characterize the piezoelectric module in order to optimize energy-harvesting efficiency. Second, we developed an integrated sensor system with the optimized energy harvester. An adaptive power knob is designated to adjust the power consumption according to energy budgeting. Finally, we intensively evaluated the ePave system in real-world applications to examine the system’s performance and explore the trade-off. Full article

(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)

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1352 KiB

Open AccessArticle

Energy-Saving Traffic Scheduling in Hybrid Software Defined Wireless Rechargeable Sensor Networks

by Yunkai Wei, Xiaohui Ma, Ning Yang and Yijin Chen

Sensors 2017, 17(9), 2126; https://doi.org/10.3390/s17092126 - 15 Sep 2017

Cited by 11 | Viewed by 4414

Abstract

Software Defined Wireless Rechargeable Sensor Networks (SDWRSNs) are an inexorable trend for Wireless Sensor Networks (WSNs), including Wireless Rechargeable Sensor Network (WRSNs). However, the traditional network devices cannot be completely substituted in the short term. Hybrid SDWRSNs, where software defined devices and traditional [...] Read more.

Software Defined Wireless Rechargeable Sensor Networks (SDWRSNs) are an inexorable trend for Wireless Sensor Networks (WSNs), including Wireless Rechargeable Sensor Network (WRSNs). However, the traditional network devices cannot be completely substituted in the short term. Hybrid SDWRSNs, where software defined devices and traditional devices coexist, will last for a long time. Hybrid SDWRSNs bring new challenges as well as opportunities for energy saving issues, which is still a key problem considering that the wireless chargers are also exhaustible, especially in some rigid environment out of the main supply. Numerous energy saving schemes for WSNs, or even some works for WRSNs, are no longer suitable for the new features of hybrid SDWRSNs. To solve this problem, this paper puts forward an Energy-saving Traffic Scheduling (ETS) algorithm. The ETS algorithm adequately considers the new characters in hybrid SDWRSNs, and takes advantage of the Software Defined Networking (SDN) controller’s direct control ability on SDN nodes and indirect control ability on normal nodes. The simulation results show that, comparing with traditional Minimum Transmission Energy (MTE) protocol, ETS can substantially improve the energy efficiency in hybrid SDWRSNs for up to 20–40% while ensuring feasible data delay. Full article

(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)

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1778 KiB

Open AccessArticle

Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks

by Ya Gao, Wenchi Cheng and Hailin Zhang

Sensors 2017, 17(9), 1933; https://doi.org/10.3390/s17091933 - 23 Aug 2017

Cited by 7 | Viewed by 5230

Abstract

Energy harvesting, which offers a never-ending energy supply, has emerged as a prominent technology to prolong the lifetime and reduce costs for the battery-powered wireless sensor networks. However, how to improve the energy efficiency while guaranteeing the quality of service (QoS) for energy [...] Read more.

Energy harvesting, which offers a never-ending energy supply, has emerged as a prominent technology to prolong the lifetime and reduce costs for the battery-powered wireless sensor networks. However, how to improve the energy efficiency while guaranteeing the quality of service (QoS) for energy harvesting based wireless sensor networks is still an open problem. In this paper, we develop statistical delay-bounded QoS-driven power control policies to maximize the effective energy efficiency (EEE), which is defined as the spectrum efficiency under given specified QoS constraints per unit harvested energy, for energy harvesting based wireless sensor networks. For the battery-infinite wireless sensor networks, our developed QoS-driven power control policy converges to the Energy harvesting Water Filling (E-WF) scheme and the Energy harvesting Channel Inversion (E-CI) scheme under the very loose and stringent QoS constraints, respectively. For the battery-finite wireless sensor networks, our developed QoS-driven power control policy becomes the Truncated energy harvesting Water Filling (T-WF) scheme and the Truncated energy harvesting Channel Inversion (T-CI) scheme under the very loose and stringent QoS constraints, respectively. Furthermore, we evaluate the outage probabilities to theoretically analyze the performance of our developed QoS-driven power control policies. The obtained numerical results validate our analysis and show that our developed optimal power control policies can optimize the EEE over energy harvesting based wireless sensor networks. Full article

(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)

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5540 KiB

Open AccessArticle

Evolutionary Beamforming Optimization for Radio Frequency Charging in Wireless Rechargeable Sensor Networks

by Ke-Han Yao, Jehn-Ruey Jiang, Chung-Hsien Tsai and Zong-Syun Wu

Sensors 2017, 17(8), 1918; https://doi.org/10.3390/s17081918 - 20 Aug 2017

Cited by 4 | Viewed by 5934

Abstract

This paper investigates how to efficiently charge sensor nodes in a wireless rechargeable sensor network (WRSN) with radio frequency (RF) chargers to make the network sustainable. An RF charger is assumed to be equipped with a uniform circular array (UCA) of 12 antennas [...] Read more.

This paper investigates how to efficiently charge sensor nodes in a wireless rechargeable sensor network (WRSN) with radio frequency (RF) chargers to make the network sustainable. An RF charger is assumed to be equipped with a uniform circular array (UCA) of 12 antennas with the radius λ, where λ is the RF wavelength. The UCA can steer most RF energy in a target direction to charge a specific WRSN node by the beamforming technology. Two evolutionary algorithms (EAs) using the evolution strategy (ES), namely the Evolutionary Beamforming Optimization (EBO) algorithm and the Evolutionary Beamforming Optimization Reseeding (EBO-R) algorithm, are proposed to nearly optimize the power ratio of the UCA beamforming peak side lobe (PSL) and the main lobe (ML) aimed at the given target direction. The proposed algorithms are simulated for performance evaluation and are compared with a related algorithm, called Particle Swarm Optimization Gravitational Search Algorithm-Explore (PSOGSA-Explore), to show their superiority. Full article

(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)

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503 KiB

Open AccessArticle

Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer

by Hongyan Yu, Yongqiang Zhang, Songtao Guo, Yuanyuan Yang and Luyue Ji

Sensors 2017, 17(8), 1906; https://doi.org/10.3390/s17081906 - 18 Aug 2017

Cited by 28 | Viewed by 6286

Abstract

Recently, the simultaneous wireless information and power transfer (SWIPT) technique has been regarded as a promising approach to enhance performance of wireless sensor networks with limited energy supply. However, from a green communication perspective, energy efficiency optimization for SWIPT system design has not [...] Read more.

Recently, the simultaneous wireless information and power transfer (SWIPT) technique has been regarded as a promising approach to enhance performance of wireless sensor networks with limited energy supply. However, from a green communication perspective, energy efficiency optimization for SWIPT system design has not been investigated in Wireless Rechargeable Sensor Networks (WRSNs). In this paper, we consider the tradeoffs between energy efficiency and three factors including spectral efficiency, the transmit power and outage target rate for two different modes, i.e., power splitting (PS) and time switching modes (TS), at the receiver. Moreover, we formulate the energy efficiency maximization problem subject to the constraints of minimum Quality of Service (QoS), minimum harvested energy and maximum transmission power as non-convex optimization problem. In particular, we focus on optimizing power control and power allocation policy in PS and TS modes to maximize energy efficiency of data transmission. For PS and TS modes, we propose the corresponding algorithm to characterize a non-convex optimization problem that takes into account the circuit power consumption and the harvested energy. By exploiting nonlinear fractional programming and Lagrangian dual decomposition, we propose suboptimal iterative algorithms to obtain the solutions of non-convex optimization problems. Furthermore, we derive the outage probability and effective throughput from the scenarios that the transmitter does not or partially know the channel state information (CSI) of the receiver. Simulation results illustrate that the proposed optimal iterative algorithm can achieve optimal solutions within a small number of iterations and various tradeoffs between energy efficiency and spectral efficiency, transmit power and outage target rate, respectively. Full article

(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)

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6346 KiB

Open AccessArticle

Impedance Matching Antenna-Integrated High-Efficiency Energy Harvesting Circuit

by Yuharu Shinki, Kyohei Shibata, Mohamed Mansour and Haruichi Kanaya

Sensors 2017, 17(8), 1763; https://doi.org/10.3390/s17081763 - 1 Aug 2017

Cited by 25 | Viewed by 7707

Abstract

This paper describes the design of a high-efficiency energy harvesting circuit with an integrated antenna. The circuit is composed of series resonance and boost rectifier circuits for converting radio frequency power into boosted direct current (DC) voltage. The measured output DC voltage is [...] Read more.

This paper describes the design of a high-efficiency energy harvesting circuit with an integrated antenna. The circuit is composed of series resonance and boost rectifier circuits for converting radio frequency power into boosted direct current (DC) voltage. The measured output DC voltage is 5.67 V for an input of 100 mV at 900 MHz. Antenna input impedance matching is optimized for greater efficiency and miniaturization. The measured efficiency of this antenna-integrated energy harvester is 60% for −4.85 dBm input power and a load resistance equal to 20 kΩ at 905 MHz. Full article

(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)

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8381 KiB

Open AccessArticle

An Adaptive Impedance Matching Network with Closed Loop Control Algorithm for Inductive Wireless Power Transfer

by Zhidong Miao, Dake Liu and Chen Gong

Sensors 2017, 17(8), 1759; https://doi.org/10.3390/s17081759 - 1 Aug 2017

Cited by 7 | Viewed by 6712

Abstract

For an inductive wireless power transfer (IWPT) system, maintaining a reasonable power transfer efficiency and a stable output power are two most challenging design issues, especially when coil distance varies. To solve these issues, this paper presents a novel adaptive impedance matching network [...] Read more.

For an inductive wireless power transfer (IWPT) system, maintaining a reasonable power transfer efficiency and a stable output power are two most challenging design issues, especially when coil distance varies. To solve these issues, this paper presents a novel adaptive impedance matching network (IMN) for IWPT system. In our adaptive IMN IWPT system, the IMN is automatically reconfigured to keep matching with the coils and to adjust the output power adapting to coil distance variation. A closed loop control algorithm is used to change the capacitors continually, which can compensate mismatches and adjust output power simultaneously. The proposed adaptive IMN IWPT system is working at 125 kHz for 2 W power delivered to load. Comparing with the series resonant IWPT system and fixed IMN IWPT system, the power transfer efficiency of our system increases up to 31.79% and 60% when the coupling coefficient varies in a large range from 0.05 to 0.8 for 2 W output power. Full article

(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)

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10956 KiB

Open AccessArticle

A Long-Distance RF-Powered Sensor Node with Adaptive Power Management for IoT Applications

by Matteo Pizzotti, Luca Perilli, Massimo Del Prete, Davide Fabbri, Roberto Canegallo, Michele Dini, Diego Masotti, Alessandra Costanzo, Eleonora Franchi Scarselli and Aldo Romani

Sensors 2017, 17(8), 1732; https://doi.org/10.3390/s17081732 - 28 Jul 2017

Cited by 38 | Viewed by 8701

Abstract

We present a self-sustained battery-less multi-sensor platform with RF harvesting capability down to −17 dBm and implementing a standard DASH7 wireless communication interface. The node operates at distances up to 17 m from a 2 W UHF carrier. RF power transfer allows operation [...] Read more.

We present a self-sustained battery-less multi-sensor platform with RF harvesting capability down to −17 dBm and implementing a standard DASH7 wireless communication interface. The node operates at distances up to 17 m from a 2 W UHF carrier. RF power transfer allows operation when common energy scavenging sources (e.g., sun, heat, etc.) are not available, while the DASH7 communication protocol makes it fully compatible with a standard IoT infrastructure. An optimized energy-harvesting module has been designed, including a rectifying antenna (rectenna) and an integrated nano-power DC/DC converter performing maximum-power-point-tracking (MPPT). A nonlinear/electromagnetic co-design procedure is adopted to design the rectenna, which is optimized to operate at ultra-low power levels. An ultra-low power microcontroller controls on-board sensors and wireless protocol, to adapt the power consumption to the available detected power by changing wake-up policies. As a result, adaptive behavior can be observed in the designed platform, to the extent that the transmission data rate is dynamically determined by RF power. Among the novel features of the system, we highlight the use of nano-power energy harvesting, the implementation of specific hardware/software wake-up policies, optimized algorithms for best sampling rate implementation, and adaptive behavior by the node based on the power received. Full article

(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)

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511 KiB

Open AccessArticle

Extending Wireless Rechargeable Sensor Network Life without Full Knowledge

by Najeeb W. Najeeb and Carrick Detweiler

Sensors 2017, 17(7), 1642; https://doi.org/10.3390/s17071642 - 17 Jul 2017

Cited by 18 | Viewed by 5461

Abstract

When extending the life of Wireless Rechargeable Sensor Networks (WRSN), one challenge is charging networks as they grow larger. Overcoming this limitation will render a WRSN more practical and highly adaptable to growth in the real world. Most charging algorithms require a priori [...] Read more.

When extending the life of Wireless Rechargeable Sensor Networks (WRSN), one challenge is charging networks as they grow larger. Overcoming this limitation will render a WRSN more practical and highly adaptable to growth in the real world. Most charging algorithms require a priori full knowledge of sensor nodes’ power levels in order to determine the nodes that require charging. In this work, we present a probabilistic algorithm that extends the life of scalable WRSN without a priori power knowledge and without full network exploration. We develop a probability bound on the power level of the sensor nodes and utilize this bound to make decisions while exploring a WRSN. We verify the algorithm by simulating a wireless power transfer unmanned aerial vehicle, and charging a WRSN to extend its life. Our results show that, without knowledge, our proposed algorithm extends the life of a WRSN on average 90% of what an optimal full knowledge algorithm can achieve. This means that the charging robot does not need to explore the whole network, which enables the scaling of WRSN. We analyze the impact of network parameters on our algorithm and show that it is insensitive to a large range of parameter values. Full article

(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)

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578 KiB

Open AccessArticle

Adaptive Data Aggregation and Compression to Improve Energy Utilization in Solar-Powered Wireless Sensor Networks

by Ikjune Yoon, Hyeok Kim and Dong Kun Noh

Sensors 2017, 17(6), 1226; https://doi.org/10.3390/s17061226 - 27 May 2017

Cited by 27 | Viewed by 6244

Abstract

A node in a solar-powered wireless sensor network (WSN) collects energy when the sun shines and stores it in a battery or capacitor for use when no solar power is available, in particular at night. In our scheme, each tiny node in a [...] Read more.

A node in a solar-powered wireless sensor network (WSN) collects energy when the sun shines and stores it in a battery or capacitor for use when no solar power is available, in particular at night. In our scheme, each tiny node in a WSN periodically determines its energy budget, which takes into account its residual energy, and its likely acquisition and consumption. If it expects to acquire more energy than it can store, the data which has it has sensed is aggregated with data from other nodes, compressed, and transmitted. Otherwise, the node continues to sense data, but turns off its wireless communication to reduce energy consumption. We compared several schemes by simulation. Our scheme reduced the number of nodes forced to black out due to lack of energy so that more data arrives at the sink node. Full article

(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)

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290 KiB

Open AccessArticle

Simultaneous Wireless Power Transfer and Secure Multicasting in Cooperative Decode-and-Forward Relay Networks

by Jong-Ho Lee, Illsoo Sohn and Yong-Hwa Kim

Sensors 2017, 17(5), 1128; https://doi.org/10.3390/s17051128 - 16 May 2017

Cited by 3 | Viewed by 4648

Abstract

In this paper, we investigate simultaneous wireless power transfer and secure multicasting via cooperative decode-and-forward (DF) relays in the presence of multiple energy receivers and eavesdroppers. Two scenarios are considered under a total power budget: maximizing the minimum harvested energy among the energy [...] Read more.

In this paper, we investigate simultaneous wireless power transfer and secure multicasting via cooperative decode-and-forward (DF) relays in the presence of multiple energy receivers and eavesdroppers. Two scenarios are considered under a total power budget: maximizing the minimum harvested energy among the energy receivers under a multicast secrecy rate constraint; and maximizing the multicast secrecy rate under a minimum harvested energy constraint. For both scenarios, we solve the transmit power allocation and relay beamformer design problems by using semidefinite relaxation and bisection technique. We present numerical results to analyze the energy harvesting and secure multicasting performances in cooperative DF relay networks. Full article

(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)

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1209 KiB

Open AccessArticle

Low-Latency and Energy-Efficient Data Preservation Mechanism in Low-Duty-Cycle Sensor Networks

by Chan Jiang, Tao-Shen Li, Jun-Bin Liang and Heng Wu

Sensors 2017, 17(5), 1051; https://doi.org/10.3390/s17051051 - 6 May 2017

Cited by 17 | Viewed by 4474

Abstract

Similar to traditional wireless sensor networks (WSN), the nodes only have limited memory and energy in low-duty-cycle sensor networks (LDC-WSN). However, different from WSN, the nodes in LDC-WSN often sleep most of their time to preserve their energies. The sleeping feature causes serious [...] Read more.

Similar to traditional wireless sensor networks (WSN), the nodes only have limited memory and energy in low-duty-cycle sensor networks (LDC-WSN). However, different from WSN, the nodes in LDC-WSN often sleep most of their time to preserve their energies. The sleeping feature causes serious data transmission delay. However, each source node that has sensed data needs to quickly disseminate its data to other nodes in the network for redundant storage. Otherwise, data would be lost due to its source node possibly being destroyed by outer forces in a harsh environment. The quick dissemination requirement produces a contradiction with the sleeping delay in the network. How to quickly disseminate all the source data to all the nodes with limited memory in the network for effective preservation is a challenging issue. In this paper, a low-latency and energy-efficient data preservation mechanism in LDC-WSN is proposed. The mechanism is totally distributed. The data can be disseminated to the network with low latency by using a revised probabilistic broadcasting mechanism, and then stored by the nodes with LT (Luby Transform) codes, which are a famous rateless erasure code. After the process of data dissemination and storage completes, some nodes may die due to being destroyed by outer forces. If a mobile sink enters the network at any time and from any place to collect the data, it can recover all of the source data by visiting a small portion of survived nodes in the network. Theoretical analyses and simulation results show that our mechanism outperforms existing mechanisms in the performances of data dissemination delay and energy efficiency. Full article

(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)

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999 KiB

Open AccessArticle

Secrecy Performance Analysis of Cognitive Sensor Radio Networks with an EH-Based Eavesdropper

by Aiwei Sun, Tao Liang and Bolun Li

Sensors 2017, 17(5), 1026; https://doi.org/10.3390/s17051026 - 4 May 2017

Cited by 8 | Viewed by 4307

Abstract

Security and privacy are crucial for cognitive sensor radio networks (CSRNs) due to the possible eavesdropping between secondary sensors and the secondary fusion center. Motivated by this observation, we investigate the physical layer security performance of CSRNs with an external energy harvesting (EH)-based [...] Read more.

Security and privacy are crucial for cognitive sensor radio networks (CSRNs) due to the possible eavesdropping between secondary sensors and the secondary fusion center. Motivated by this observation, we investigate the physical layer security performance of CSRNs with an external energy harvesting (EH)-based eavesdropper. Considering the underlay working paradigm of CSRNs, the transmit power of the secondary sensor node must be adjusted to guarantee the quality-of-service (

Q o S

) of the primary user. Hence, two different interference power constraint scenarios are studied in this paper. To give an intuitive insight into the secrecy performance of the considered wiretap scenarios, we have derived the closed-form analytical expressions of secrecy outage probability for both of the considered cases. Monte Carlo simulation results are also performed to verify the theoretical analysis derived, and show the effect of various parameters on the system performance. Full article

(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)

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2182 KiB

Open AccessArticle

Optimal Power Control in Wireless Powered Sensor Networks: A Dynamic Game-Based Approach

by Haitao Xu, Chao Guo and Long Zhang

Sensors 2017, 17(3), 547; https://doi.org/10.3390/s17030547 - 9 Mar 2017

Cited by 16 | Viewed by 4940

Abstract

In wireless powered sensor networks (WPSN), it is essential to research uplink transmit power control in order to achieve throughput performance balancing and energy scheduling. Each sensor should have an optimal transmit power level for revenue maximization. In this paper, we discuss a [...] Read more.

In wireless powered sensor networks (WPSN), it is essential to research uplink transmit power control in order to achieve throughput performance balancing and energy scheduling. Each sensor should have an optimal transmit power level for revenue maximization. In this paper, we discuss a dynamic game-based algorithm for optimal power control in WPSN. The main idea is to use the non-cooperative differential game to control the uplink transmit power of wireless sensors in WPSN, to extend their working hours and to meet QoS (Quality of Services) requirements. Subsequently, the Nash equilibrium solutions are obtained through Bellman dynamic programming. At the same time, an uplink power control algorithm is proposed in a distributed manner. Through numerical simulations, we demonstrate that our algorithm can obtain optimal power control and reach convergence for an infinite horizon. Full article

(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)

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1751 KiB

Open AccessArticle

A Temperature-Dependent Battery Model for Wireless Sensor Networks

by Leonardo M. Rodrigues, Carlos Montez, Ricardo Moraes, Paulo Portugal and Francisco Vasques

Sensors 2017, 17(2), 422; https://doi.org/10.3390/s17020422 - 22 Feb 2017

Cited by 40 | Viewed by 7472

Abstract

Energy consumption is a major issue in Wireless Sensor Networks (WSNs), as nodes are powered by chemical batteries with an upper bounded lifetime. Estimating the lifetime of batteries is a difficult task, as it depends on several factors, such as operating temperatures and [...] Read more.

Energy consumption is a major issue in Wireless Sensor Networks (WSNs), as nodes are powered by chemical batteries with an upper bounded lifetime. Estimating the lifetime of batteries is a difficult task, as it depends on several factors, such as operating temperatures and discharge rates. Analytical battery models can be used for estimating both the battery lifetime and the voltage behavior over time. Still, available models usually do not consider the impact of operating temperatures on the battery behavior. The target of this work is to extend the widely-used Kinetic Battery Model (KiBaM) to include the effect of temperature on the battery behavior. The proposed Temperature-Dependent KiBaM (T-KiBaM) is able to handle operating temperatures, providing better estimates for the battery lifetime and voltage behavior. The performed experimental validation shows that T-KiBaM achieves an average accuracy error smaller than 0.33%, when estimating the lifetime of Ni-MH batteries for different temperature conditions. In addition, T-KiBaM significantly improves the original KiBaM voltage model. The proposed model can be easily adapted to handle other battery technologies, enabling the consideration of different WSN deployments. Full article

(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)

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Review

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12157 KiB

Open AccessReview

Review of Batteryless Wireless Sensors Using Additively Manufactured Microwave Resonators

by Muhammad Usman Memon and Sungjoon Lim

Sensors 2017, 17(9), 2068; https://doi.org/10.3390/s17092068 - 9 Sep 2017

Cited by 4 | Viewed by 9441

Abstract

The significant improvements observed in the field of bulk-production of printed microchip technologies in the past decade have allowed the fabrication of microchip printing on numerous materials including organic and flexible substrates. Printed sensors and electronics are of significant interest owing to the [...] Read more.

The significant improvements observed in the field of bulk-production of printed microchip technologies in the past decade have allowed the fabrication of microchip printing on numerous materials including organic and flexible substrates. Printed sensors and electronics are of significant interest owing to the fast and low-cost fabrication techniques used in their fabrication. The increasing amount of research and deployment of specially printed electronic sensors in a number of applications demonstrates the immense attention paid by researchers to this topic in the pursuit of achieving wider-scale electronics on different dielectric materials. Although there are many traditional methods for fabricating radio frequency (RF) components, they are time-consuming, expensive, complicated, and require more power for operation than additive fabrication methods. This paper serves as a summary/review of improvements made to the additive printing technologies. The article focuses on three recently developed printing methods for the fabrication of wireless sensors operating at microwave frequencies. The fabrication methods discussed include inkjet printing, three-dimensional (3D) printing, and screen printing. Full article

(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)

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