Anita, Latsmi Manohar (2019) A security-enhanced cluster size adjustment scheme for cognitive radio networks. Masters thesis, Sunway University.
Full text not available from this repository.Abstract
Cognitive radio network (CRN) is the next-generation wireless network that allows unlicensed users (or secondary users, SUs) to explore and use the underutilised licensed channels (or white spaces) owned by licensed users (or primary users, PUs). The purpose is to increase spectrum utilization for enhanced network performance. Clustering segregates SUs in a CRN into logical groups (or clusters) with each consisting of a leader (or cluster head) and member nodes. A budget-based cluster size adjustment scheme is applied to enable each cluster to adjust its number of member nodes in its cluster based on the availability of white spaces in order to improve network scalability. However, cluster size adjustment is prone to attacks by malicious SUs that launch random and intelligent attacks. Hence, we incorporate an artificial intelligence (AI) approach called reinforcement learning (RL) into a trust model to countermeasure the random and intelligent attacks. Simulation results show that RL-based trust model increases the utilisation of white spaces (reducing wastage of white spaces) and increases cluster size to improve network scalability and enhance network performance despite the presence of RL-based intelligent attacks.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | CRN; |
| Subjects: | Q Science > Q Science (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Sunway University > School of Engineering and Technology [formerly School of Science and Technology until 2020] > Dept. Computer Sciences & Networked System [dissolved] |
| Depositing User: | Ms Yong Yee Chan |
| Date Deposited: | 27 Sep 2023 07:40 |
| Last Modified: | 27 Sep 2023 07:40 |
| URI: | http://eprints.sunway.edu.my/id/eprint/2396 |
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