Dynamic Spectrum Sensing for Energy Harvesting Wireless Sensor

2013 ◽  
Author(s):  
Yuki Mizutani ◽  
Manabu Sato ◽  
Yuusuke Kawakita ◽  
Haruhisa Ichikawa
Keyword(s):  
Energy Harvesting ◽  
Spectrum Sensing ◽  
Dynamic Spectrum ◽  
Wireless Sensor

scholarly journals A joint optimization of energy harvesting and spectrum sensing for wireless sensor networks under Middleton Class A noise

2018 ◽  
Vol 14 (5) ◽  
pp. 155014771877766
Author(s):  
Enwei Xu ◽  
Shuo Shi ◽  
Dawei Chen ◽  
Xuemai Gu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Harvesting ◽  
Spectrum Sensing ◽  
Lower Order ◽  
Wireless Sensor ◽  
Joint Optimization ◽  
Order Moment ◽  
Average Throughput ◽  
Class A

With the growing popularity of wireless sensor networks, the environment in which the network is located becomes more undesirable. In addition, the problems of spectrum scarcity and the short sensor lifetime have become increasingly prominent. In this article, we incorporate the two technologies of cognitive radio and energy harvesting to solve the above problems of wireless sensor networks under impulsive noise. First, we use a Middleton Class A noise model to imitate the practical environment and the fractional lower order moments detector is employed to perform spectrum sensing for the sensors of wireless sensor networks, which are performing as the second users. Second, a new time-slots structure is proposed for the self-powered second user and the analytical expression of the second user’s average throughput is derived. Finally, we maximize the second user’s average throughput by a joint optimization of the sensing duration and data transmission duration while giving the primary user sufficient protection. Simulation shows that a much better performance can be achieved by fractional lower order moment detector than the traditional energy detector. Moreover, our optimization of the time-slots allocation is feasible and the maximum second user’s average throughput can be obtained.

Wireless Sensor Network in IoT and Performance Optimization

2020 ◽  
Vol 13 ◽  
Author(s):  
Sunita Gupta ◽  
Sakar Gupta ◽  
Dinesh Goyal
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Energy Harvesting ◽  
Performance Optimization ◽  
Design Space ◽  
Life Time ◽  
Wireless Sensor ◽  
Topology Management ◽  
Management Application ◽  
Energy Latency

: A serious problem in Wireless Sensor Networks (WSNs) is to attain high-energy efficiency as battery is used to power and have limited stored energy. They can’t be suitably replaced or recharged. Appearance of renewable energy harvesting techniques and their combination with sensor devices gives Energy Harvesting Wireless Sensor Networks (EHWSNs). IoT is now becoming part of our lives, comforting simplifying our routines and work life. IoT is very popular . It connects together, computes, communicates and performs the required task. IoT is actually a network of physical devices or things that can interact with each other to share information. This paper gives an overview of WSN and IoT, related work, different ways of connecting WSN with internet, development of smart home, challenges for WSN etc. Next a Framework for performance optimization in IoT is given and QC-PC-MCSC heuristic is analyzed in terms of Energy Efficiency and Life Time of a sensor on Energy Latency Density Design Space, a topology management application that is power efficient. QC-PC-MCSC and QC-MCSC are compared for Energy Efficiency and Life Time of a sensor over energy latency density design space, a topology management application.

scholarly journals Sensor System: A Survey of Sensor Type, Ad Hoc Network Topology and Energy Harvesting Techniques

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 219
Author(s):  
Phuoc Duc Nguyen ◽  
Lok-won Kim
Keyword(s):  
Energy Harvesting ◽  
Large Scale ◽  
Ad Hoc ◽  
Sensor Nodes ◽  
Sensor System ◽  
Wireless Sensor ◽  
The Internet ◽  
Original Research ◽  
Energy Scavenging ◽  
Term Operation

People nowadays are entering an era of rapid evolution due to the generation of massive amounts of data. Such information is produced with an enormous contribution from the use of billions of sensing devices equipped with in situ signal processing and communication capabilities which form wireless sensor networks (WSNs). As the number of small devices connected to the Internet is higher than 50 billion, the Internet of Things (IoT) devices focus on sensing accuracy, communication efficiency, and low power consumption because IoT device deployment is mainly for correct information acquisition, remote node accessing, and longer-term operation with lower battery changing requirements. Thus, recently, there have been rich activities for original research in these domains. Various sensors used by processing devices can be heterogeneous or homogeneous. Since the devices are primarily expected to operate independently in an autonomous manner, the abilities of connection, communication, and ambient energy scavenging play significant roles, especially in a large-scale deployment. This paper classifies wireless sensor nodes into two major categories based the types of the sensor array (heterogeneous/homogeneous). It also emphasizes on the utilization of ad hoc networking and energy harvesting mechanisms as a fundamental cornerstone to building a self-governing, sustainable, and perpetually-operated sensor system. We review systems representative of each category and depict trends in system development.

scholarly journals A Self-Powered PMFC-Based Wireless Sensor Node for Smart City Applications

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Daniel Ayala-Ruiz ◽  
Alejandro Castillo Atoche ◽  
Erica Ruiz-Ibarra ◽  
Edith Osorio de la Rosa ◽  
Javier Vázquez Castillo
Keyword(s):  
Energy Harvesting ◽  
Low Power ◽  
Sensor Node ◽  
Smart Cities ◽  
Cloud Services ◽  
Environmental Data ◽  
Security And Privacy ◽  
Wireless Sensor ◽  
Ultra Low Power ◽  
Self Powered

Long power wide area networks (LPWAN) systems play an important role in monitoring environmental conditions for smart cities applications. With the development of Internet of Things (IoT), wireless sensor networks (WSN), and energy harvesting devices, ultra-low power sensor nodes (SNs) are able to collect and monitor the information for environmental protection, urban planning, and risk prevention. This paper presents a WSN of self-powered IoT SNs energetically autonomous using Plant Microbial Fuel Cells (PMFCs). An energy harvesting device has been adapted with the PMFC to enable a batteryless operation of the SN providing power supply to the sensor network. The low-power communication feature of the SN network is used to monitor the environmental data with a dynamic power management strategy successfully designed for the PMFC-based LoRa sensor node. Environmental data of ozone (O3) and carbon dioxide (CO2) are monitored in real time through a web application providing IoT cloud services with security and privacy protocols.

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