Improving Energy Efficiency of Mobile WSN Using Reconfigurable Directional Antennas

Le, Thanh Long; Pégatoquet, Alain; Trinh, Le Huy; Lizzi, Léonardo; Ferrero, Fabien

doi:10.1109/lcomm.2016.2554544

Cited by 49 publications

(23 citation statements)

References 4 publications

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“…Some of the protocols proposed also require multiple channels to successfully operate [8,13,16]. Only a few papers within the literature [14,[17][18][19] have considered the energy consumption of the protocol, which is an important factor for low power nodes [20].…”

Section: Of 16mentioning

confidence: 99%

Virtual Sensing Directional Hub MAC (VSDH-MAC) Protocol with Power Control

et al. 2020

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Medium access control (MAC) protocols play a vital role in making effective use of a multiple access channel as it governs the achievable performance such as channel utilization and corresponding quality of service of wireless sensor networks (WSNs). In this paper, a virtual carrier sensing directional hub (VSDH) MAC protocol incorporating realistic directional antenna patterns is proposed for directional single hub centralized WSNs. While in most instances, MAC protocols assume idealized directional antenna patterns, the proposed VSDH-MAC protocol incorporates realistic directional antenna patterns to deliver enhanced link performance. We demonstrate that the use of directional antennas with a suitable MAC protocol can provide enhanced communication range and increased throughput with reduced energy consumption at each node, compared to the case when only omnidirectional antennas are used. For the scenarios considered in this study, results show that the average transmit power of the sensor nodes can be reduced by a factor of two, and at the same time offer significantly extended lifetime.

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Section: Of 16mentioning

confidence: 99%

Virtual Sensing Directional Hub MAC (VSDH-MAC) Protocol with Power Control

et al. 2020

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“…Harsh interference would impose a significant impact on the quality and reliability of data [38]. In recent years, Research on improving anti-interference performance has made some progress [39]: for example, the noise reduction method [40], calculation of interference intensities [41,42] and noise reduction algorithms, such as the adaptive stochastic resonance filter [43] and Hilbert time-time (IHTT) transformations [44]. But they are unavailable for transformer FRA procedures because there exist only slight differences between the FR curves.…”

Section: Introductionmentioning

confidence: 99%

Anti-Interference Deep Visual Identification Method for Fault Localization of Transformer Using a Winding Model

Duan

et al. 2019

Sensors

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The idea of Ubiquitous Power Internet of Things (UPIoTs) accelerates the development of intelligent monitoring and diagnostic technologies. In this paper, a diagnostic method suitable for power equipment in an interference environment was proposed based on the deep Convolutional Neural Network (CNN): MobileNet-V2 and Digital Image Processing (DIP) methods to conduct fault identification process: including fault type classification and fault localization. A data visualization theory was put forward in this paper, which was applied in frequency response (FR) curves of transformer to obtain dataset. After the image augmentation process, the dataset was input into the deep CNN: MobileNet-V2 for training procedures. Then a spatial-probabilistic mapping relationship was established based on traditional Frequency Response Analysis (FRA) fault diagnostic method. Each image in the dataset was compared with the fingerprint values to get traditional diagnosing results. Next, the anti-interference abilities of the proposed CNN-DIP method were compared with that of the traditional one while the magnitude of the interference gradually increased. Finally, the fault tolerance of the proposed method was verified by further analyzing the deviations between the wrong diagnosing results with the corresponding actual labels. Experimental results showed that the proposed deep visual identification (CNN-DIP) method has a higher diagnosing accuracy, a stronger anti-interference ability and a better fault tolerance.

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“…This permits a significant reduction in collision and interference packets [6,7]. Moreover, it can help to extend the range of communication between nodes, allowing the possibility of using a smaller number of nodes within the monitoring area.…”

Section: Introductionmentioning

confidence: 99%

Directive and Reconfigurable Loaded Antenna Array for Wireless Sensor Networks

Dihissou

Diallo

Thuc

et al. 2018

PIER C

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Abstract-In this paper, a four switchable beam antenna dedicated to Wireless Sensor Network (WSN) nodes in the 2.4 ISM band (2.4-2.485 GHz) is presented. It consists of two fed monopoles and two loaded parasitic ones. The nature and value of the load are obtained using the Uzkov equations, allowing to determine current weighting coefficients in the case of two separately fed antennas, in order to maximize the gain and the directivity in a given direction. Reconfigurability is achieved using reflector and director elements activated by PIN diodes to reduce the back radiation and pointing in the desired direction. Thus, a first system is obtained which consists of two elements, one fed and the other loaded with an inductor, with a maximum gain of 5.2 dBi in simulation and 4.7 dBi measured at 2.4 GHz in azimuthal directions of 90 • and 270 • . Then, the system is compared with another, composed of two antennas fed separately. Finally, the same methodology is applied to an array of four antennas, in which two antennas are fed, and two are loaded. This last structure is capable of steering its radiation pattern in the azimuth plane, covering a 360 • angle with four beams (0 • , 90 • , 180 • and 270 • ). The total gain achieved is 4 dBi for each beam in the azimuth plane.

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Improving Energy Efficiency of Mobile WSN Using Reconfigurable Directional Antennas

Cited by 49 publications

References 4 publications

Virtual Sensing Directional Hub MAC (VSDH-MAC) Protocol with Power Control

Virtual Sensing Directional Hub MAC (VSDH-MAC) Protocol with Power Control

Anti-Interference Deep Visual Identification Method for Fault Localization of Transformer Using a Winding Model

Directive and Reconfigurable Loaded Antenna Array for Wireless Sensor Networks

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