scholarly journals An Energy Efficient Cooperative Spectrum Sensing for Cognitive Radio-Internet of Things with Interference Constraints

2021 ◽  
Author(s):  
Md Sipon Miah ◽  
Mohammad Amzad Hossain ◽  
Kazi Mowdud Ahmed ◽  
Md. Mahbubur Rahman ◽  
Ali Calhan
Keyword(s):  
Cognitive Radio ◽  
Internet Of Things ◽  
Spectrum Sensing ◽  
Energy Efficient ◽  
Cooperative Spectrum Sensing ◽  
Final Decision ◽  
Weight Factor ◽  
Interference Constraints ◽  
Leibler Divergence ◽  
Local Decision

Abstract Spectrum sensing plays a very important role in Cognitive Radio based Internet of Things (CR-IoT) networks for utilization of the licensed spectrum accurately. However, the performance of the conventional Energy Detector (ED) method is compromised in a noise-uncertain environment owing to interference constraints, i.e. the CR-IoT user interference with the licensed Primary User (PU) on the same licensed band. To overcome this drawback, we proposed an energy efficient Cooperative Spectrum Sensing (CSS) for a CR-IoT network with interference constraints using a novel ED method. In this method, each CR-IoT user is capable of spectrum sensing that makes both the local decision and the weight factor based on the sequential approach; we calculate the weight factor against each CR-IoT user based on the Kullback Leibler Divergence award score. After the local decision and the weight factor are made, each CR-IoT user transmits its measured both the local decisions, and the weight factor to a Fusion Center (FC), which is made a final decision about the PU activities based on the hard fusion rule. The simulation results demonstrates that the proposed ED method obtains an improved detection performance, an enhanced sum rate, a spectral efficiency, an energy efficiency, and a lower global error probability when compared to other conventional ED methods under time varying environments.

scholarly journals Enhanced Sensing and Sum-Rate Analysis in a Cognitive Radio-Based Internet of Things

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2525 ◽  
Author(s):  
Md. Sipon Miah ◽  
Kazi Mowdud Ahmed ◽  
Md. Khairul Islam ◽  
Md. Ashek Raihan Mahmud ◽  
Md. Mahbubur Rahman ◽  
...  
Keyword(s):  
Cognitive Radio ◽  
Internet Of Things ◽  
Spectrum Sensing ◽  
Energy Detection ◽  
Uncertain Environment ◽  
Detection Techniques ◽  
Leibler Divergence ◽  
Local Decision ◽  
Sum Rate ◽  
Sensing Performance

Spectrum sensing plays a vital role in cognitive radio networks (CRNs) for identifying the spectrum hole. However, an individual cognitive radio user in a CRN does not obtain sufficient sensing performance and sum rate of the primary and secondary links to support the future Internet of Things (IoT) using conventional detection techniques such as the energy detection (ED) technique in a noise-uncertain environment. In an environment comprising noise uncertainty, the performance of conventional energy detection techniques is significantly degraded owing to the noise fluctuation caused by the noise temperature, interference, and filtering. To mitigate this problem, we present a cooperative spectrum sensing technique that comprises the use of the Kullback–Leibler divergence (KLD) in cognitive radio-based IoT (CR-IoT). In the proposed method, each unlicensed IoT device that is capable of spectrum sensing, which is called a CR-IoT user, makes a local decision using the KLD technique. The spectrum sensing performed with the KLD requires a smaller number of samples than other conventional approaches, e.g., energy detection, for reliable sensing even in a noise uncertain environment. After the local decision is made, each CR-IoT user sends its own local decision result to the corresponding fusion center, which makes a global decision using the soft fusion rule. The results obtained through simulations show that the proposed KLD scheme achieves a better sensing performance, i.e., higher detection and lower false-alarm probabilities, enhances the sum rate, and reduces the total time as compared to the conventional ED scheme under various fading channels.

scholarly journals Cooperative spectrum sensing based on adaptive activation of energy and preamble detector for cognitive radio networks

2018 ◽  
Vol 7 ◽  
Author(s):  
Ashish Rauniyar ◽  
Soo Young Shin
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Energy Efficient ◽  
Cooperative Spectrum Sensing ◽  
Signal To Noise Ratio ◽  
Radio Networks ◽  
Second Step ◽  
Time Simulation ◽  
Local Decision

In this paper, we propose a new cooperative spectrum sensing method based on adaptive activation of energy detector (ED) and preamble detector (PD) for cognitive radio networks. The ED performance is highly degraded under low signal to noise ratio and noise uncertainty condition. To alleviate the problem of ED and increase the sensing performance, we have used adaptive activation of energy efficient ED and reliable PD. As the first step of our proposed method, we have used ED to take a decision in the clear region where the detector can easily make its own local decision. There are two thresholds for the measured energy in the first step. If the sensed energy in the first step is between these two thresholds, the second step which involves the activation of cooperative PD is triggered to make an appropriate decision on the presence or absence of primary users's signal. Otherwise, the second step detector PD is not activated. In this way, we can enhance the detection performance and energy efficiency by taking the collaborative advantages of ED and PD at the same time. Simulation results validate the effectiveness of our proposed method as compared with conventional schemes.

Energy-Efficient Cooperative Spectrum Sensing by Optimal Scheduling in Sensor-Aided Cognitive Radio Networks

2012 ◽  
Vol 61 (2) ◽  
pp. 716-725 ◽  
Author(s):  
Ruilong Deng ◽  
Jiming Chen ◽  
Chau Yuen ◽  
Peng Cheng ◽  
Youxian Sun
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Energy Efficient ◽  
Cooperative Spectrum Sensing ◽  
Radio Networks ◽  
Optimal Scheduling

Joint optimal energy-efficient cooperative spectrum sensing and transmission in cognitive radio

2017 ◽  
Vol 14 (1) ◽  
pp. 98-110 ◽  
Author(s):  
Weizhi Zhong ◽  
Kunqi Chen ◽  
Xin Liu
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Energy Efficient ◽  
Cooperative Spectrum Sensing ◽  
Optimal Energy

Performance analysis of superior selective reporting-based energy efficient cooperative spectrum sensing in cognitive radio networks

2017 ◽  
Vol 65 ◽  
pp. 99-116 ◽  
Author(s):  
Rajalekshmi Kishore ◽  
Ramesha C.K. ◽  
Sanjeev Gurugopinath ◽  
Anupama K.R.
Keyword(s):  
Cognitive Radio ◽  
Performance Analysis ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Energy Efficient ◽  
Cooperative Spectrum Sensing ◽  
Radio Networks ◽  
Selective Reporting

scholarly journals Towards energy-efficient cooperative spectrum sensing for cognitive radio networks: an overview

2014 ◽  
Vol 59 (1) ◽  
pp. 77-91 ◽  
Author(s):  
Saud Althunibat ◽  
Marco Di Renzo ◽  
Fabrizio Granelli
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Energy Efficient ◽  
Cooperative Spectrum Sensing ◽  
Radio Networks
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