Felix Obite
Papers
1
Total Citations
51
H-Index
1
About
Felix Obite is a researcher at the forefront of applying artificial intelligence to wireless communications, with a particular focus on cognitive radio networks. His work bridges the gap between advanced machine learning techniques and practical spectrum management challenges. Obite’s most cited contribution, "An overview of deep reinforcement learning for spectrum sensing in cognitive radio networks" (2021), has garnered 51 citations, establishing him as a key voice in this rapidly evolving field. In this seminal review, he systematically explores how deep reinforcement learning can enable dynamic, intelligent spectrum access—a critical need for next-generation wireless systems. By synthesizing state-of-the-art algorithms and identifying open research problems, Obite has provided a foundational resource for both newcomers and experienced engineers. His work is notable for its clarity and practical orientation, offering a roadmap for integrating AI into real-world cognitive radio architectures. With a growing citation footprint, Obite’s research continues to influence how we design more efficient, adaptive, and autonomous wireless networks, making him a rising authority in the intersection of deep learning and spectrum intelligence.
Research Focus
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Top Papers
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