scholarly journals Effect of Clusters in Energy-Efficient Cooperative White Space Detection in a Cognitive Radio System

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Samson I Ojo ◽  
Zachaeus K Adeyemo ◽  
Damilare O Akande ◽  
Rebecca O Omowaiye
Keyword(s):  
Cognitive Radio ◽  
Spectral Efficiency ◽  
Energy Efficient ◽  
Fusion Rule ◽  
Probability Of Detection ◽  
White Space ◽  
Radio System ◽  
Cognitive Radio System ◽  
Individual Cluster ◽  
Sensing Time

White Space Detection (WSD) is a core operation in a Cognitive Radio System (CRS) to identify idle spectrum for maximum utilization. However, WSD is often affected by multipath effects resulting in poor detection rate. Cooperative WSD (CWSD) which is one of the existing techniques used to address the problem is characterized by long sensing time, energy and bandwidth inefficiency. Energy-Efficient CWSD (EECWSD) was proposed in previous work to solve the problem associated with CWSD. Hence, in this paper, the effect of clusters in EECWSD is carried out with Radiometry Detector (RD). The investigation is carried out using multiple clusters and each cluster contained multiple Secondary Users (SUs). The SUs are used to perform local sensing and the sensing results are combined at individual cluster using majority fusion rule. The sensing results from individual cluster are combined to obtain global sensing result using OR fusion rule. The system is simulated using MATLAB software. The system is evaluated using Probability of Detection (PD), Total Error Probability (TEP), Spectral Efficiency (SE) and Sensing Time (ST). At SNR of 20 dB, PD values of 0.7890, 0.8376 and 0.8787 are obtained for clusters 3, 4 and 5, respectively, while the corresponding TEP values are 0.2210, 0.1724 and 0.1313 for clusters 3, 4 and 5, respectively. At SNR of 16 dB, 13.2594 and 16.4341 are the SE values obtained for clusters 3 and 5, respectively, while the corresponding ST values obtained are 4.2487 and 2.6177 s for clusters 3 and 5, respectively. The results obtained revealed that, PD and SE increase as number of cluster increases, while ST and TEP reduce as cluster increases.  Keywords— Cognitive Radio, White Space, Spectrum Sensing, Probability of Detection, Spectral Efficiency.

scholarly journals Energy-Efficient Cluster-Based Cooperative Spectrum Sensing in a Multiple Antenna Cognitive Radio Network

2021 ◽  
pp. 176-185
Author(s):  
Samson I. Ojo ◽  
◽  
Zachaeus K. Adeyemo ◽  
Damilare O. Akande ◽  
Ayobami O. Fawole
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Energy Efficient ◽  
Cooperative Spectrum Sensing ◽  
Cluster Head ◽  
Fusion Rule ◽  
Probability Of Detection ◽  
Multiple Antenna ◽  
Secondary Users ◽  
Sensing Time

Spectrum Hole Detection (SHD) is a major operation in a Cognitive Radio (CR) network to identify empty spectrum for maximum utilization. However, SHD is often affected by multipath effects resulting in interference. The existing techniques used to address these problems are faced by poor detection rate, long sensing time and bandwidth inefficiency. Hence, this paper proposes a cluster-based Energy-Efficient Multiple Antenna Cooperative Spectrum Sensing (EEMACSS) for SHD in CR networks using Energy Detector (ED) with a modified combiner. Multiple secondary users are used to carry out local sensing using ED in multiple antenna configurations. The local sensing results are combined at the cluster head using majority fusion rule to determine the sensing results at each cluster. The sensing results from individual cluster are combined to determine the global sensing result using OR fusion rule. The proposed EEMACSS is evaluated using Probability of Detection (PD), Sensing Time (ST) and Spectral Efficiency (SE) by comparing with existing techniques. The results reveal that the proposed technique shows better performance.

A hybrid model for energy efficient spectrum sensing in cognitive radio

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahua Bhowmik ◽  
P. Malathi P. Malathi
Keyword(s):  
Cognitive Radio ◽  
Prediction Model ◽  
Spectrum Sensing ◽  
Hybrid Model ◽  
Energy Efficient ◽  
Probability Of Detection ◽  
Content Type ◽  
Hybrid Prediction ◽  
Probability Of False Alarm ◽  
Sensing Time

Purpose Cognitive radio (CR) plays a very important role in enabling spectral efficiency in wireless communication networks, where the secondary user (SU) allows the licensed primary users (PUs). The purpose of this paper is to develop a prediction model for spectrum sensing in CR. Design/methodology/approach This paper proposes a hybrid prediction model, called krill-herd whale optimization-based actor critic neural network and hidden Markov model (KHWO-ACNN-HMM). The spectral bands are determined optimally using the proposed hybrid prediction model for allocating the spectrum bands to the PUs. For better sensing, the eigenvalue based on cooperative sensing used in CR. Finally, a hybrid model is designed by hybridizing KHWO-ACNN and HMM to enhance the accuracy of sensing. The predicted results of KHWO-ACNN and HMM are combined by a fusion model, for which a weighted entropy fusion is employed to determine the free spectrum available in CRs. Findings The performance of the prediction model is evaluated based on metrics, such as probability of detection, probability of false alarm, throughput and sensing time. The proposed spectrum sensing method achieves maximum probability of detection of 0.9696, minimum probability of false alarm rate as 0.78, minimum throughput of 0.0303 and the maximum sensing time of 650.08 s. Research implications The proposed method is useful in various applications, including authentication applications, wireless medical networks and so on. Originality/value A hybrid prediction model is introduced for energy efficient spectrum sensing in CR and the performance of the proposed model is evaluated with the existing models. The proposed hybrid model outperformed the other techniques.

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