AI DRIVEN ANTENNA DESIGN FOR NEXT-GENERATION: 6G AND BEYOND

  • Associate Professor, UG Student, Dept. of ECE, Pragati Engineering College (A), Surampalem, Kakinada, Andhra Pradesh, India.
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The transition to sixth-generation (6G) communication networks is unlocking new horizons for applications including immersive extended reality, autonomous mobility, holographic telepresence, and massive Internet of Things (IoT). Such demands can be addressed with antenna systems that provide increased efficiency, faster agility, and consistent performance across difficult environments. Conventional design techniques,although successful in previous generations,are increasingly constricted when dealing with the intricacy of multi band, reconfigurable, and high-frequency antennas. Here, we discuss how artificial intelligence (AI) can transform the antenna design process. With the integration of data-driven learning and physics-driven understanding, AI methods such as machine learning and reinforcement learning can accelerate design cycles, enhance precision, and optimize factors such as gain, beamforming, and radiation patterns. We also present case studies at millimeter-wave (mmWave) and terahertz (THz) frequencies that show quantifiable improvements over traditional methods. The research indicates that AI-based approaches not only improve performance but also offer adaptable and scalable solutions that best fit the changing demands of 6G and beyond.


Dr.V.Radhika, Sai Teja Rama Reddy Mallidi, Shaik Ahmed Mastan Nawaz, Pavan Srinadheluri, Tarun Veera Venkat Guthula and Jason Ram Potnuru (2026); AI DRIVEN ANTENNA DESIGN FOR NEXT-GENERATION: 6G AND BEYOND, Int. J. of Adv. Res., 14 (01), 284-291, ISSN 2320-5407. DOI URL: https://dx.doi.org/10.21474/IJAR01/22235


Zahoor Ahmad Pir

India

DOI:


Article DOI: 10.21474/IJAR01/22235      
DOI URL: https://dx.doi.org/10.21474/IJAR01/22235