scholarly journals An Improved Clustering Cooperative Spectrum Sensing Algorithm Based on Modified Double-Threshold Energy Detection and Its Optimization in Cognitive Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Shubin Wang ◽  
Huiqin Liu ◽  
Kun Liu
Keyword(s):  
Wireless Sensor Networks ◽  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Threshold Energy ◽  
Energy Detection ◽  
Wireless Sensor ◽  
Cognitive Wireless Sensor Networks ◽  
Double Threshold ◽  
Sensing Performance ◽  
Improved Algorithm

Cooperative spectrum sensing (CSS) is a very important technique in cognitive wireless sensor networks, but the channel and multipath affect the sensing performance. For improving the sensing performance, this paper incorporates a modified double-threshold energy detection (MDTED) and the location and channel information to improve the clustering cooperative spectrum sensing (CCSS) algorithm. Within each cluster, the cognitive node with the best channel quality to the fusion center (FC) is chosen as the cluster head (CH), and each node uses the MDTED. The detective information is sent to CH, and CH makes the decision of the cluster. The decision information is sent to FC by each CH, and FC uses the “or” rule to fuse all clusters’ decision information and makes a final decision. Since MDTED needs to transfer large traffic and occupy channel widely, this paper further optimizes the improved algorithm. Ensuring the detection performance, the cognitive nodes participating in the sensing are properly reduced. Simulation results show that the detecting accuracy of the improved algorithm is higher than conventional CSS, and the improved algorithm can also significantly improve collaborative sensing ability. For the optimization of cognitive nodes’ number, the detection probability of the network can be obviously increased.

scholarly journals A Robust and Energy Efficient Cooperative Spectrum Sensing Scheme in Cognitive Wireless Sensor Networks

2015 ◽  
Vol 7 (3) ◽  
pp. 140 ◽  
Author(s):  
Shaoyang Men ◽  
Pascal Chargé ◽  
Sébastien Pillement
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Spectrum Sensing ◽  
Energy Efficient ◽  
Evaluation Method ◽  
Cooperative Spectrum Sensing ◽  
Wireless Sensor ◽  
Hidden Terminal ◽  
Cognitive Wireless Sensor Networks

Cooperative spectrum sensing (CSS) is able to effectively solve the hidden terminal, depth attenuation, multipath shadows and other issues which are not addressed by the single-user sensing. Therefore, it has attracted a large amount of interest and several CSS algorithms have been proposed. However, they are not specifically tailored for cognitive wireless sensor networks (CWSNs) where transmission reliability, power management and interference avoidance are critical issues. In this paper, we propose a robust and energy efficient CSS scheme in CWSNs. Firstly, taking into account the limited energy of sensor node, especially the mobile node, we introduce the nodes of the network into multiple clusters for the CSS in order to save energy consumed in reporting results and exchanging information and extend the lifetime of the network. Secondly, we consider that some cognitive nodes may not work as expected. Hence, facing the problem of faulty nodes in clusters, we propose an evaluation method which considers simultaneously the node reliability and the mutually supportive degree among different nodes to support adapted decisions. Finally, after removing the node of low credibility, the energy efficiency and reliability of each cluster are improved significantly. Simulation results allow to validate that the proposed method outperforms the state of the art in energy efficiency and detection reliability, even in presence of faulty nodes.

scholarly journals Adaptive Double-Threshold Cooperative Spectrum Sensing Algorithm Based on History Energy Detection

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Shanshan Yu ◽  
Ju Liu ◽  
Jing Wang ◽  
Inam Ullah
Keyword(s):  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Signal To Noise Ratio ◽  
Threshold Energy ◽  
Average Energy ◽  
Energy Detection ◽  
Detection Performance ◽  
Weighting Coefficient ◽  
Threshold Method ◽  
Double Threshold

Spectrum sensing is one of the key technologies in the field of cognitive radio, which has been widely studied. Among all the sensing methods, energy detection is the most popular because of its simplicity and no requirement of any prior knowledge of the signal. In the case of low signal-to-noise ratio (SNR), the traditional double-threshold energy detection method employs fixed thresholds and there is no detection result when the energy is between high and low thresholds, which leads to poor detection performance such as lower detection probability and longer spectrum sensing time. To address these problems, we proposed an adaptive double-threshold cooperative spectrum sensing algorithm based on history energy detection. In each sensing period, we calculate the weighting coefficient of thresholds according to the SNR of all cognitive nodes; thus, the upper and lower thresholds can be adjusted adaptively. Furthermore, in a single cognitive node, once the current energy is within the high and low thresholds, we utilize the average energy of history sensing times to rejudge. To ensure the real-time performance, if the average history energy is still between two thresholds, the single-threshold method will be used for the end decision. Finally, the fusion center aggregates the detection results of each node and obtains the final cooperative conclusion through “or” criteria. Theoretical analysis and simulation results show that the algorithm proposed in this paper improved detection performance significantly compared with the other four different double-threshold algorithms.

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