International Journal of Research and Development in Engineering Sciences https://www.ijrdes.com Pudi Ganesh 2 3 (May - June) 2020 06 May-June enCognitive Radio NetworksSpectrum AllocationMachine LearningDynamic Spectrum AccessWireless CommunicationSpectrum Efficiency The rapid growth of wireless communication has led to an increased demand for radio spectrum resulting in inefficient spectrum utilization and congestion in conventional networks Cognitive Radio Networks CRNs offer a promising solution by enabling dynamic and intelligent spectrum access through spectrum sensing learning and adaptation This paper focuses on intelligent spectrum allocation in CRNs using machine learning and optimization techniques to enhance spectral efficiency and reduce interference The proposed system enables secondary users to opportunistically utilize underused frequency bands without disrupting primary users Algorithms such as reinforcement learning and fuzzy logic are applied to predict spectrum availability and allocate channels dynamically based on realtime network conditions Simulation results show that intelligent allocation mechanisms improve throughput minimize latency and ensure fair spectrum sharing among users This study contributes to developing adaptive selflearning communication systems capable of addressing spectrum scarcity in nextgeneration wireless networks Copyright (c) 2026 International Journal of Research and Development in Engineering Sciences. All rights reserved. 2020 All Rights Reserved