scholarly journals Low-Power Beam-Switching Technique for Power-Efficient Collaborative IoT Edge Devices

2021 ◽  
Vol 11 (4) ◽  
pp. 1608
Author(s):  
Semyoung Oh ◽  
Daejin Park
Keyword(s):  
Energy Consumption ◽  
Antenna Arrays ◽  
Optimization Problem ◽  
Signal To Noise Ratio ◽  
Optimal Combination ◽  
Wireless Sensor ◽  
Greedy Search ◽  
Signal To Noise ◽  
Power Efficient ◽  
Beam Switching

Collaborative beamforming (CB) enables uplink transmission in a wireless sensor network (WSN) composed of sensors (nodes) and far-away access points (APs). It can also be applied to the case where the sensors are equipped with beam-switching structures (BSSs). However, as the antenna arrays of the BSSs are randomly headed due to the irregular mounting surface, some sensors form beams that do not illuminate a desired AP and waste their limited energy. Therefore, to resolve this problem, it is required to switch the beams toward the desired AP. While an exhaustive search can provide the globally optimal combination, a greedy search (GS) is utilized to solve this optimization problem efficiently. Simulation and experimental results verify that under certain conditions the proposed algorithm can drive the sensors to switch their beams properly and increase the received signal-to-noise ratio (SNR) significantly with low computational complexity and energy consumption.

Применение адаптивного анизотропного диффузного фильтра для повышения качества изображения отражателей при проведении ультразвукового неразрушающего контроля

2021 ◽  
pp. 3-12
Author(s):  
Е.Г. Базулин
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Antenna Arrays ◽  
Human Factor ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Efficient Operation ◽  
Optical Images ◽  
Segmentation Methods ◽  
Segmentation Of Images

Currently, in order to increase the speed of preparing the ultrasound control protocol and reduce the influence of the human factor, systems for recognizing (classifying) reflectors based on artificial neural networks are being actively developed. For their more efficient operation, the images of the reflectors need to be worked on in order to increase the signal-to-noise ratio of the image and its segmentation (clustering). One of the segmentation methods is to process the image with an adaptive anisotropic diffuse filter, which is used to process optical images. In model experiments, the effectiveness of using this texture filter for segmentation of images of reflectors reconstructed from echo signals measured using antenna arrays is demonstrated.

scholarly journals An SNR-Optimized Scanning Strategy for Geostationary Carbon Cycle Observatory (GeoCarb) Instrument

2018 ◽  
Author(s):  
Jeffrey Nivitanont ◽  
Sean Crowell
Keyword(s):  
Carbon Cycle ◽  
Greenhouse Gases ◽  
Optimization Problem ◽  
Signal To Noise Ratio ◽  
Western Hemisphere ◽  
Geostationary Orbit ◽  
Signal To Noise ◽  
Scanning Strategy ◽  
Land Mass ◽  
Error Distributions

Abstract. The Geostationary Carbon Observatory (GeoCarb) will make measurements of greenhouse gases over the land mass in the western hemisphere. The extreme flexibility of observing from geostationary orbit induces an optimization problem, as operators must choose what to observe and when. We express this problem in terms of an optimal subcovering problem, and use an Incremental Optimization (IO) algorithm to create a scanning strategy that minimizes expected error as a function of the signal-to-noise ratio (SNR), and show that this method outperforms the human selected strategy in terms of global error distributions.

Nature-Inspired Algorithms in Wireless Sensor Networks

2019 ◽  
pp. 246-275
Author(s):  
Ajay Kaushik ◽  
S. Indu ◽  
Daya Gupta
Keyword(s):  
Wireless Sensor Networks ◽  
Big Data ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Sensor Node ◽  
Optimization Problem ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Nature Inspired Algorithms

Wireless sensor networks (WSNs) are becoming increasingly popular due to their applications in a wide variety of areas. Sensor nodes in a WSN are battery operated which outlines the need of some novel protocols that allows the limited sensor node battery to be used in an efficient way. The authors propose the use of nature-inspired algorithms to achieve energy efficient and long-lasting WSN. Multiple nature-inspired techniques like BBO, EBBO, and PSO are proposed in this chapter to minimize the energy consumption in a WSN. A large amount of data is generated from WSNs in the form of sensed information which encourage the use of big data tools in WSN domain. WSN and big data are closely connected since the large amount of data emerging from sensors can only be handled using big data tools. The authors describe how the big data can be framed as an optimization problem and the optimization problem can be effectively solved using nature-inspired algorithms.

scholarly journals Uplink Resource Allocation in Device-to-Device Communication System

2018 ◽  
Vol 246 ◽  
pp. 03003
Author(s):  
Xiuwei Han ◽  
Xin Song ◽  
Dong Li ◽  
Jingpu Wang
Keyword(s):  
Resource Allocation ◽  
Power Control ◽  
Channel Assignment ◽  
Optimization Problem ◽  
Signal To Noise Ratio ◽  
System Capacity ◽  
Optimal Selection ◽  
Resource Allocation Problem ◽  
Selection Algorithm ◽  
Signal To Noise

In this paper, we study uplink resource allocation problem to maximize the overall system capacity while guaranteeing the signal-to-noise ratio of both D2D users and cellular users (CUs). The optimization problem can be decomposed into two subproblems: power control and channel assignment. We first prove that the objective function of power control problem is a convex function to get the optimal transmit power. Then, we design an optimal selection algorithm for channel assignment. Numerical results reveal the proposed scheme is capable of improving the system’s performance compared with the random selection algorithm.

scholarly journals A new hybrid architecture with an intersection-based coverage algorithm in wireless sensor networks

2014 ◽  
Vol 11 (3) ◽  
pp. 1017-1035 ◽  
Author(s):  
Young-Long Chen ◽  
Mu-Yen Chen ◽  
Fu-Kai Cheung ◽  
Yung-Chi Chang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sleep Mode ◽  
Hybrid Architecture ◽  
Power Efficient ◽  
Adaptive Clustering ◽  
Average Distribution

Energy is limited in wireless sensor networks (WSNs) so that energy consumption is very important. In this paper, we propose a hybrid architecture based on power-efficient gathering in sensor information system (PEGASIS) and low-energy adaptive clustering hierarchy (LEACH). This architecture can achieve an average distribution of energy loads, and reduced energy consumption in transmission. To further extend the system lifetime, we combine the intersection-based coverage algorithm (IBCA) with LEACH architecture and the hybrid architecture to prolong the system lifetime that introducing sensor nodes to enter sleep mode when inactive. This step can save more energy consumption. Simulation results show that the performance of our proposed LEACH architecture with IBCA and the hybrid architecture with IBCA perform better than LEACH architecture with PBCA in terms of energy efficiency, surviving nodes and sensing areas.

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