Radio frequency energy harvesting from ambient FM signals for making battery-less sensor nodes for wireless sensor networks

In wireless sensor networks powered by battery-limited energy harvesting, sensor nodes that have relatively more energy can help other sensor nodes reduce their energy consumption by compressing the sensing data packets in order to consequently extend the network lifetime. In this article, we consider a data compression technique that can shorten the data packet itself to reduce the energies consumed for packet transmission and reception and to eventually increase the entire network lifetime. First, we present an energy consumption model, in which the energy consumption at each sensor node is derived. We then propose a data compression algorithm that determines the compression level at each sensor node to decrease the total energy consumption depending on the average energy level of neighboring sensor nodes while maximizing the lifetime of multihop wireless sensor networks with energy harvesting. Numerical simulations show that the proposed algorithm achieves a reduced average energy consumption while extending the entire network lifetime.

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Design and Implementation of a Dual-Band Rectifier Antenna for Efficient RF Energy Harvesting in Wireless Sensor Networks

Journal of Circuits System and Computers ◽

10.1142/s0218126619500348 ◽

2018 ◽

Vol 28 (02) ◽

pp. 1950034 ◽

Cited By ~ 2

Author(s):

Asmita Rajawat ◽

P. K. Singhal

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Energy Harvesting ◽

Sensor Nodes ◽

Wireless Sensor ◽

Dual Band ◽

Slot Antenna ◽

Design System ◽

Rf Energy Harvesting ◽

Rf Energy

Wireless sensor networks (WSN) have observed an exponential amount of growth in the recent past. The energy associated with the sensor nodes is limited which is a major bottleneck for the WSN technologies. The sensor nodes in WSN need to be continuously charged and thus an efficient RF energy harvesting needs to be explored. In the proposed design, a dual-band rectifier antenna for RF energy harvesting has been developed for 900 MHz and 2.45 GHz frequencies as RF energy is mainly available in the range of 900 MHz–2.45 GHz. The antenna proposed is microstrip U slot antenna with S11 parameter below −10 dB at 2.45 GHz and 0.8 GHz with a gain of 5.1 dBi and 10.1 dBi at 900 MHz and 2.45 GHz, respectively. The circuit for the rectifier uses Schottky Diode HSMS-285C for the purpose of rectification. The rectifier circuit used is a Greinacher Voltage Multiplier. Impedance Matching of the rectifier has been processed out to improve the performance of the circuit. Simulations of rectifier have been done on Advanced Design System (ADS) Software. The conversion efficiency at 900 MHz and 2.45 GHz is found to be 78.7% and 51.768%, respectively. The proposed design can find its uses in large number of energy harvesting applications under wireless power transmission such as powering of Wireless Sensor Nodes.

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Modified Echo State Network Enabled Dynamic Duty Cycle for Optimal Opportunistic Routing in EH-WSNs

Electronics ◽

10.3390/electronics9010098 ◽

2020 ◽

Vol 9 (1) ◽

pp. 98

Author(s):

Rajkumar Singh Rathore ◽

Suman Sangwan ◽

Kabita Adhikari ◽

Rupak Kharel

Keyword(s):

Wireless Sensor Networks ◽

Energy Consumption ◽

Sensor Networks ◽

Energy Harvesting ◽

Duty Cycle ◽

Opportunistic Routing ◽

Sensor Nodes ◽

Wireless Sensor ◽

Echo State Network ◽

Proposed Model

Minimizing energy consumption is one of the major challenges in wireless sensor networks (WSNs) due to the limited size of batteries and the resource constrained tiny sensor nodes. Energy harvesting in wireless sensor networks (EH-WSNs) is one of the promising solutions to minimize the energy consumption in wireless sensor networks for prolonging the overall network lifetime. However, static energy harvesting in individual sensor nodes is normally limited and unbalanced among the network nodes. In this context, this paper proposes a modified echo state network (MESN) based dynamic duty cycle with optimal opportunistic routing (OOR) for EH-WSNs. The proposed model is used to act as a predictor for finding the expected energy consumption of the next slot in dynamic duty cycle. The model has adapted a whale optimization algorithm (WOA) for optimally selecting the weights of the neurons in the reservoir layer of the echo state network towards minimizing energy consumption at each node as well as at the network level. The adapted WOA enabled energy harvesting model provides stable output from the MESN relying on optimal weight selection in the reservoir layer. The dynamic duty cycle is updated based on energy consumption and optimal threshold energy for transmission and reception at bit level. The proposed OOR scheme uses multiple energy centric parameters for selecting the relay set oriented forwarding paths for each neighbor nodes. The performance analysis of the proposed model in realistic environments attests the benefits in terms of energy centric metrics such as energy consumption, network lifetime, delay, packet delivery ratio and throughput as compared to the state-of-the-art-techniques.

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A Review on Conservation of Energy in Wireless Sensor Networks

International Journal of Smart Sensor Technologies and Applications ◽

10.4018/ijssta.2020040101 ◽

2020 ◽

Vol 1 (2) ◽

pp. 1-16

Author(s):

Oluwadara J. Odeyinka ◽

Opeyemi A. Ajibola ◽

Michael C. Ndinechi ◽

Onyebuchi C. Nosiri ◽

Nnaemeka Chiemezie Onuekwusi

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Energy Harvesting ◽

Data Communication ◽

Sensor Nodes ◽

Wireless Sensor ◽

Energy Usage ◽

Wireless Sensor Nodes ◽

Conservation Of Energy ◽

Battery Energy

This paper is a review on energy conservation in wireless sensor networks (WSNs). Due to the nature of wireless sensor nodes in terms of deployment and their common usage in terrains with limited access, recharging or replacing sensor nodes batteries may be difficult. This paper examined various sources of energy in WSNs Battery, energy harvesting and energy transference. Also, various energy usage operations and energy wastage activities in WSNs were examined, and comparisons of different routing protocols based on network structure, energy dissipation, data communication cost, and entire energy usage in WSNs were itemized. The prospects of the machine learning (ML) approach in addressing energy constraint issues in WSNs were reviewed. This paper recommends a compound approach in routing decisions to maximize energy usage operation and minimize energy wastage activities, consideration for energy harvesting and transference mechanisms, and exploring the potentials in ML algorithms to resolve energy problem in wireless sensor networks.

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A Routing Protocol for Solar Energy Harvesting Wireless Sensor Networks

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.734-737.2903 ◽

2013 ◽

Vol 734-737 ◽

pp. 2903-2906

Author(s):

He Pei Li ◽

Ling Tao Zhang ◽

Su Bo He

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Energy Harvesting ◽

Solar Energy ◽

Routing Protocol ◽

Average Energy ◽

Sensor Nodes ◽

Wireless Sensor ◽

Data Delivery ◽

Solar Energy Harvesting

Energy and lifetime issues are crucial to the wide applications of wireless sensor networks. This paper proposes a routing protocol, SEHRP (Solar Energy Harvesting Routing Protocol), for solar energy harvesting wireless sensor networks. This protocol classifies all the sensor nodes into various regions for which each region has been assigned its transmission priority, and the data can only be delivered from lower priority regions to higher priority region. SEHRP can also detect the sensor nodes which are under the charging state, then avoid choosing those charging nodes to ensure the successful data delivery. Simulation results show that, compared to the baseline protocol, SEHRP can achieve significant performance improvements in terms of average energy consumption and average data delivery rate.

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