AI-Powered Beamforming for Next-Gen Wireless Systems

Authors

  • Rajasree Yandra, Prasad Rayi, Rama Subbanna, Sakthivel S

Keywords:

AI-based Beamforming, Smart Antenna Systems, Next-Generation Wireless Networks, 5G and 6G, Technologies, Machine Learning in Wireless Communication, Signal Processing Optimization, Real-time Network Adaptation

Abstract

The rapid progression of wireless communication technology has profoundly influenced contemporary culture, enabling unparalleled connectedness and data transmission. As the need for elevated data rates, improved dependability, and reduced latency intensifies, the constraints of current network infrastructures become more apparent.
Next-generation wireless networks, including 5G and the anticipated 6G, seek to address these difficulties by using sophisticated technology such as AI-driven beamforming and intelligent antenna systems. Beamforming improves signal strength and minimizes interference by directing wireless signals to particular receiving devices, therefore greatly enhancing service quality in metropolitan environments. Smart antenna systems enhance network performance by dynamically modifying their patterns according to real-time circumstances. The use of artificial intelligence (AI) in these systems facilitates advanced real-time analysis, forecasting, and decision-making capacities, crucial for overseeing the intricate and evolving characteristics of next-generation networks. This study examines the use of AI-driven beamforming and intelligent antenna design in next-generation wireless networks. The paper illustrates the efficacy of AI-driven strategies in improving network performance via comprehensive theoretical analysis and practical applications, including case studies. Significant results indicate that AI-augmented models attain up to 95% accuracy in fault identification, a 30% enhancement in process optimization, and a 20% decrease in maintenance expenses relative to conventional techniques. The research emphasizes the practical advantages and possibilities of using AI into semiconductor production processes. This study enhances the development and optimization of wireless communication technologies by addressing both technical and practical factors, therefore supporting the overarching objective of attaining ubiquitous and seamless connection.

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References

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Published

30.10.2024

How to Cite

Rajasree Yandra. (2024). AI-Powered Beamforming for Next-Gen Wireless Systems. International Journal of Intelligent Systems and Applications in Engineering, 12(4), 5598 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/7482

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Section

Research Article