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R. Kumar

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Open access Aug 2026

DEEP REINFORCEMENT LEARNING-BASED DYNAMIC SPECTRUM ACCESS FOR 6G HETEROGENEOUS COGNITIVE RADIO NETWORKS

A Deep Reinforcement Learning (DRL)-based framework for dynamic spectrum access in 6G heterogeneous Cognitive Radio Networks (Het-CRNs), wherein secondary users learn optimal channel selection policies through direct interaction with the radio environment, without requiring explicit statistical channel models is proposed.

Naadir Kamal, R. Kumar · 0 citations

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