Title: Reinforcement learning-driven collective intelligence for prioritised spectrum reservation in cognitive radio network

Authors: Meetu Nag; Bhanu Pratap

Addresses: Department of Electronics and Communication Engineering, Poornima College of Engineering, Jaipur, India ' Department of Mechanical Engineering, Poornima Institute of Engineering and Technology, Jaipur, India

Abstract: In the realm of cognitive radio networks, research aims to enhance spectrum usage by enabling access for more users through different spectrum allocation policies. The dynamic and rapid changes in the communication environment pose challenges in making correct decision for spectrum allocation. To facilitate dynamic spectrum allocation, intelligence is integrated into the cognitive system to analyse environmental parameters, various known parameters have to be analysed to know about the nature of the radio node. In this paper a novel method is discussed for spectrum allocation by involving a multiple decision system that works on priority-based allocation approach. This system collects environmental data for decision-making, ensuring efficient service in this adaptive communication scenario.

Keywords: reinforcement learning; collective intelligence; spectrum reservation in cognitive radio network; spectrum sensing; cognitive radio network; CRN.

DOI: 10.1504/IJRIS.2026.155199

International Journal of Reasoning-based Intelligent Systems, 2026 Vol.18 No.4, pp.220 - 226

Received: 08 Oct 2024
Accepted: 30 Nov 2024
Published online: 29 Jul 2026 *

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