Improved Whale Optimization Algorithm and Convolutional neural network based Cooperative Spectrum Sensing in Cognitive Radio Networks

ABSTRACT

In this manuscript, we establish a Cognitive Radio Network (CRN) based on Cooperative Spectrum Sensors (CSS) with Improved Whale Optimization Algorithm (IWOA). In our work, the main users are provided for the support of multiple cooperating secondary users. To obtain, the computed particular exposure samples spatial and spectral correlation is utilized. To instruct the particular exposure samples of the secondary user, the convolutional neural network (CNN)-based Cooperative Spectrum Sensors (CSS) framework is used. An Improved Whale Optimization Algorithm (IWOA) is comprised to calculate the weight function of CNN optimally raises the accuracy. A weight of inertia for Whale Optimization Algorithm (WOA) used to perform the WOA (IWOA). Finally, the primary user of the CNN structure can accurately perceive. Assessment metrics are performed based on delay, delivery ratio, energy consumption, impartiality index, and performance parameters. According to the proposed method, accuracy is 95.36%.

KEYWORDS:

• Cognitive Radio Network (CRN)
• Cooperative Spectrum Sensors (CSS)
• Improved Whale Optimization Algorithm (IWOA)
• convolutional neural network (CNN)