Abstract
Cognitive Radio (CR) Network is a wireless communication technology, in which a detection device smartly detects occupied and unoccupied channels. During traffic, unused primary user spectrum space is allotted to a secondary user, without causing any intervention with the primary user. Though this has reduced network traffic to a great extent, many issues related to security has became an alarming problem, in which the primary user’s space is misused by some malicious secondary users without the knowledge of primary user. To address this issue, in this paper we have proposed a Boundary detection method that uses the estimated location of each SU, which is obtained using the Recurrent Neural Network algorithm, to determine the boundary of PU coverage. Then Malicious User Detection by Ordering (MUDO) methodology is proposed, in which all secondary users are weighed using Basic Probability Analysis (BPA), and based on the orders the SUs are paired with corresponding PUs. The SUs with the least orders are discarded as they might be malicious users. The proposed methodology possesses higher detection speed and precise detection thereby enhancing the performance of CR.
Highlights
Cognitive Radio (CR) is a widely used wireless radio communication to utilize the available spectrum space of licensed users (Primary Users) efficiently
The primary Users (PU) unused spectrum space for a particular period is allocated to the Secondary Users (SU)
The most alarming issue in this assignment is security, in which the secondary users disguise as primary users and misuses the allotted spectrum
Summary
Cognitive Radio (CR) is a widely used wireless radio communication to utilize the available spectrum space of licensed users (Primary Users) efficiently. This work is licensed under a Creative Commons Attribution 4.0 International
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