Machine Learning Algorithms for Adaptive Beamforming in Smart Antenna Systems
| Authors | A.P. Kumar1, Kali Varaprasad B2, P.R. Kumar3 |
| Affiliations |
1Department of AIML & ECE, CMR Engineering College, Hyderabad, India 2Department of ECE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, India 3Department of Artificial Intelligence and Machine Learning, Malla Reddy University, Hyderabad, India |
| Е-mail | pramodvce@gmail.com |
| Issue | Volume 17, Year 2025, Number 6 |
| Dates | Received 08 August 2025; revised manuscript received 17 December 2025; published online 19 December 2025 |
| Citation | A.P. Kumar, Kali Varaprasad B, P.R. Kumar, J. Nano- Electron. Phys. 17 No 6, 06017 (2025) |
| DOI | https://doi.org/10.21272/jnep.17(6).06017 |
| PACS Number(s) | 07.05.Tp, 84.40.Ba |
| Keywords | Beam forming, ANN (62) , Python, AOA. |
| Annotation |
Smart antennas are now a day’s one of the most important elements of wireless communications technology. This is because of their special characteristics and features. The future application of smart antenna technologies in wireless structures, however, will likely greatly influence spectrum use efficiency, minimize the cost of new networks, improve service quality and simplify the various wireless network technologies. Machine Learning (ML) Techniques are very efficient, powerful, and popular techniques in recent decades. In resolving various nonlinear issues that cannot be simply solved with traditional techniques, Artificial Neural Networks (ANN) have demonstrated their vast capacity to provide higher performance. In this article, the application of artificial neural networks to smart antenna systems is introduced. The most prominent adaptive beam-forming techniques are compared with the smart antenna ANN algorithm. The Python and its powerful library “matplotlib.pyplo” and “pyroomacoustics” functions will be used to decide the weights of the antenna features to decrease the error in the signal received using the ANN back propagation algorithm. |
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