N. Sureka^*, K. Gunaseelan

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1893-1906, 2022, DOI:10.32604/iasc.2022.026098

Abstract Cognitive Radio (CR) is a competent technique devised to smart sense its surroundings and address the spectrum scarcity issues in wireless communication networks. The Primary User Emulation Attack (PUEA) is one of the most serious security threats affecting the performance of CR networks. In this paper, machine learning (ML) principles have been applied to detect PUEA with superior decision-making ability. To distinguish the attacking nodes, Reinforced Learning (RL) and Extreme Machine Learning (EML-RL) algorithms are proposed to be based on Reinforced Learning (EML). Various dynamic parameters like estimation error, attack detection efficiency, attack estimation rate, and learning rate have been… More >

Imran Khan¹, Fahd N. Al-Wesabi², Marwa Obayya³, Anwer Mustafa Hilal⁴, Manar Ahmed Hamza⁴, Mohammed Rizwanullah⁴, Fahad Ahmed Al-Zahrani⁵, Hirofumi Amano⁶, Samih M. Mostafa^7,*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 697-715, 2022, DOI:10.32604/cmc.2022.021847

Abstract With the rapid development of wireless communication technology, the spectrum resources are increasingly strained which needs optimal solutions. Cognitive radio (CR) is one of the key technologies to solve this problem. Spectrum sensing not only includes the precise detection of the communication signal of the primary user (PU), but also the precise identification of its modulation type, which can then determine the a priori information such as the PU’ service category, so as to use this information to make the cognitive user (CU) aware to discover and use the idle spectrum more effectively, and improve the spectrum utilization. Spectrum sensing… More >

Zilong Jin^1,2, Chengbo Zhang¹ , Kan Yao³ , Dun Cao⁴ , Seokhoon Kim⁵, Yuanfeng Jin^6,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5991-6005, 2022, DOI:10.32604/cmc.2022.021498

Abstract

Cognitive radio devices can utilize the licensed channels in an opportunistic manner to solve the spectrum scarcity issue occurring in the unlicensed spectrum. However, these cognitive radio devices (secondary users) are greatly affected by the original users (primary users) of licensed channels. Cognitive users have to adjust operation parameters frequently to adapt to the dynamic network environment, which causes extra energy consumption. Energy consumption can be reduced by predicting the future activity of primary users. However, the traditional prediction-based algorithms require large historical data to achieve a satisfying precision accuracy which will consume a lot of time and memory space.… More >

U. Venkateshkumar^1,*, S. Ramakrishnan²

Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 817-830, 2020, DOI:10.32604/iasc.2020.010116

Abstract A hybrid form of the genetic algorithm and the modified K-Means cluster algorithm forms as a Gencluster to detect a spectrum hole among n-number of primary users (PUs) is present in the cooperative spectrum sensing model. The fusion center (FC), applies the genetic algorithm to identify the best chromosome, which contains many PUs cluster centers and by applying the modified K-Means cluster algorithm identifies the cluster with the PU vacant spectrum showing high accuracy, and maximum probability of detection with minimum false alarm rates are achieved. The graphical representation of the performance metric of the system model shows 95% accuracy… More >