Optimization of Sensing Time in Cognitive Radio Networks Based on Localization Algorithm
Cognitive radio is one of the promising technologies that allows opportunistic spectrum access for unlicensed users namely the secondary users (SUs) to utilize the white spaces available in the spectrum allocated to the primary user (PU). To achieve a power efficient spectrum sensing the geometry-based localization algorithm is proposed. Here, the deployment of primary and secondary users are first considered. Then the secondary users are categorized based on their known and unknown locations. In order to locate the unknown secondary user, within the prescribed geometry, is identified by employing the Spider Monkey Optimization algorithm. To ensure optimal convergence for the given problem statement N number of iterations are done and best values are calculated using the fitness factor of the samples. Based on the best values, the optimized location of the unknown SUs is recorded and priority is given to those SUs that remain close to the PU and maintains a proper degree of separation. Since wireless devices are more vulnerable to security threats, this paper also aims in identifying malicious nodes and prohibiting them to access the white spaces by inducing denial of service through primary user to safeguard the spectrum access by outliers. Simulation results also provide a satisfactory outcome for achieving power effective spectrum sensing and performance of the proposed algorithm is studied in the presence of malicious and normal nodes.
KeywordsSpectrum sensing Spider monkey optimization White spaces Malicious node detection
- 2.https://transition.fcc.gov/oet/spectrum/table/fcctable.pdf. Federal Communications Commission Office Of Engineering and Technology Policy and Rules Division
- 8.Yongcai, A., Bo, Z., Baozhuo, Z., Shili, W.: Change of geometric dilution of precision (GDOP) for integrated system. In: 2016 IEEE Information Technology, Networking, Electronic and Automation Control Conference, Chongqing, pp. 660–662 (2016). https://doi.org/10.1109/itnec.2016.7560443
- 11.Clancy, T.C., Goergen, N.: Security in cognitive radio networks: threats and mitigation. In: 2008 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2008), Singapore, pp. 1–8 (2008). https://doi.org/10.1109/crowncom.2008.4562534