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Implementation of AI-Driven Adaptive Antenna Systems for Smart Communication Networks
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Author(s): Pradeep Kumar Tiwari (United College of Engineering and Research, Prayagraj, India), Santosh Dubey (United College of Engineering and Research, Prayagraj, India), Ravi Srivastava (United College of Engineering and Research, Prayagraj, India), Satya Prakash Singh (United College of Engineering and Research, Prayagraj, India), Sandeep Kanaujia (United Institute of Management, Prayagraj, India)and Shadab Hussain (MathCo, Chicago, USA)
Copyright: 2026
Pages: 30
Source title:
Optimizing Automation in Engineering With Energy Systems and Communication Networks
Source Author(s)/Editor(s): Vipin Balyan (Cape Peninsula University of Technology, South Africa), Tarun Varshney (Sharda University, India), Sandeep Gupta (Graphic Era University, India)and Gunjan Gupta (Cape Peninsula University of Technology, South Africa)
DOI: 10.4018/979-8-3373-2737-2.ch003
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Abstract
The speed of progress in wireless communication requires smart, adaptive antenna systems that can enhance network performance in dynamic environments. This chapter presents AI-based adaptive antenna systems for smart communication networks. By using machine learning algorithms, the antenna adjusts beamforming and polarization in real-time to optimize signal quality, decrease interference, and increase throughput. We describe the architecture, the algorithmic framework, and the experimental validation. The results show a remarkable improvement in spectral efficiency and network reliability, highlighting the superiority of AI in future adaptive antenna technology.
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