scholarly journals An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks

Sensors ◽  
2015 ◽  
Vol 15 (8) ◽  
pp. 19783-19818 ◽  
Author(s):  
Ibrahim Mustapha ◽  
Borhanuddin Ali ◽  
Mohd Rasid ◽  
Aduwati Sali ◽  
Hafizal Mohamad
Keyword(s):  
Reinforcement Learning ◽  
Cognitive Radio ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Clustering Algorithm ◽  
Cognitive Radio Sensor Networks

scholarly journals An energy efficient Reinforcement Learning based Cooperative Channel Sensing for Cognitive Radio Sensor Networks

2017 ◽  
Vol 35 ◽  
pp. 165-184 ◽  
Author(s):  
Ibrahim Mustapha ◽  
Borhanuddin M. Ali ◽  
A. Sali ◽  
M.F.A. Rasid ◽  
H. Mohamad
Keyword(s):  
Reinforcement Learning ◽  
Cognitive Radio ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Cognitive Radio Sensor Networks ◽  
Channel Sensing

Energy Efficient Cognitive Radio Sensor Networks with Team-Based Hybrid Sensing

2019 ◽  
Vol 111 (2) ◽  
pp. 929-945 ◽  
Author(s):  
J. Bala Vishnu ◽  
M. A. Bhagyaveni
Keyword(s):  
Cognitive Radio ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Cognitive Radio Sensor Networks

Exploiting Secure and Energy-Efficient Collaborative Spectrum Sensing for Cognitive Radio Sensor Networks

2016 ◽  
Vol 15 (10) ◽  
pp. 6813-6827 ◽  
Author(s):  
Ju Ren ◽  
Yaoxue Zhang ◽  
Qiang Ye ◽  
Kan Yang ◽  
Kuan Zhang ◽  
...  
Keyword(s):  
Cognitive Radio ◽  
Sensor Networks ◽  
Spectrum Sensing ◽  
Energy Efficient ◽  
Cognitive Radio Sensor Networks ◽  
Collaborative Spectrum Sensing

EMCOS: Energy-efficient Mechanism for Multimedia Streaming over Cognitive Radio Sensor Networks

2015 ◽  
Vol 22 ◽  
pp. 16-32 ◽  
Author(s):  
Abbas Bradai ◽  
Kamal Singh ◽  
Abderrezak Rachedi ◽  
Toufik Ahmed
Keyword(s):  
Cognitive Radio ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Multimedia Streaming ◽  
Efficient Mechanism ◽  
Cognitive Radio Sensor Networks

scholarly journals Energy-Efficient Cognitive Radio Sensor Networks: Parametric and Convex Transformations

2021 ◽  
Author(s):  
Muhammad Naeem ◽  
Kandasamy Illanko ◽  
Ashok Karmokar ◽  
Alagan Anpalagan ◽  
Muhammad Jaseemuddin
Keyword(s):  
Cognitive Radio ◽  
Sensor Networks ◽  
Constrained Optimization ◽  
Power Allocation ◽  
Energy Efficient ◽  
Optimization Problem ◽  
Numerical Solutions ◽  
Sensor Nodes ◽  
Constrained Optimization Problem ◽  
Cognitive Radio Sensor Networks

Designing energy-efficient cognitive radio sensor networks is important to intelligently use battery energy and to maximize the sensor network life. In this paper, the problem of determining the power allocation that maximizes the energy-efficiency of cognitive radio-based wireless sensor networks is formed as a constrained optimization problem, where the objective function is the ratio of network throughput and the network power. The proposed constrained optimization problem belongs to a class of nonlinear fractional programming problems. Charnes-Cooper Transformation is used to transform the nonlinear fractional problem into an equivalent concave optimization problem. The structure of the power allocation policy for the transformed concave problem is found to be of a water-filling type. The problem is also transformed into a parametric form for which a ε-optimal iterative solution exists. The convergence of the iterative algorithms is proven, and numerical solutions are presented. The iterative solutions are compared with the optimal solution obtained from the transformed concave problem, and the effects of different system parameters (interference threshold level, the number of primary users and secondary sensor nodes) on the performance of the proposed algorithms are investigated.

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