scholarly journals Outage Probability Minimization for Energy Harvesting Cognitive Radio Sensor Networks

Sensors ◽  
2017 ◽  
Vol 17 (2) ◽  
pp. 224 ◽  
Author(s):  
Fan Zhang ◽  
Tao Jing ◽  
Yan Huo ◽  
Kaiwei Jiang
Keyword(s):  
Cognitive Radio ◽  
Sensor Networks ◽  
Energy Harvesting ◽  
Outage Probability ◽  
Cognitive Radio Sensor Networks

scholarly journals A Self-Learning MAC Protocol for Energy Harvesting and Spectrum Access in Cognitive Radio Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-18 ◽  
Author(s):  
Mohammed Hawa ◽  
Khalid A. Darabkh ◽  
Raed Al-Zubi ◽  
Ghazi Al-Sukkar
Keyword(s):  
Cognitive Radio ◽  
Sensor Networks ◽  
Energy Harvesting ◽  
Mac Protocol ◽  
Sensor Nodes ◽  
Distributed Mac ◽  
Data Packets ◽  
Cognitive Radio Sensor Networks ◽  
Energy Needs ◽  
The Cost

The fusion of Wireless Sensor Networks (WSNs) and Cognitive Radio Networks (CRNs) into Cognitive Radio Sensor Networks (CRSNs) is quite an attractive proposal, because it allows a distributed set of low-powered sensor nodes to opportunistically access spectrum bands that are underutilized by their licensed owners (called primary users (PUs)). In addition, when the PUs are actively transmitting in their own bands, sensor nodes can switch to energy harvesting mode to obtain their energy needs (for free), to achieve almost perpetual life. In this work, we present a novel and fully distributed MAC protocol, calledS-LEARN, that allows sensor nodes in a CRSN to entwine their RF energy harvesting and data transmission activities, while intelligently addressing the issue of disproportionate difference between the high power necessary for the node to transmit data packets and the small amount of power it can harvest wirelessly from the environment. The presented MAC protocol can improve both the network throughput and total harvested energy, while being robust to changes in the network configuration. Moreover, S-LEARN can keep the cost of the system low, and it avoids the pitfalls from which centralized systems suffer.

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