作者
Jaspreet Kaur, Satyam Bhatti, Kang Tan, Olaoluwa R Popoola, Muhammad Ali Imran, Rami Ghannam, Qammer H Abbasi, Hasan T Abbas
发表日期
2024/3/1
期刊
APL Machine Learning
卷号
2
期号
1
出版商
AIP Publishing
简介
Beamforming, an integral component of modern mobile networks, enables spatial selectivity and improves network quality. However, many beamforming techniques are iterative, introducing unwanted latency to the system. In recent times, there has been a growing interest in leveraging mobile users’ location information to expedite beamforming processes. This paper explores the concept of contextual beamforming, discussing its advantages, disadvantages, and implications. Notably, we demonstrate an impressive 53% improvement in the signal-to-interference-plus-noise ratio by implementing the adaptive beamforming maximum ratio transmission (MRT) algorithm compared to scenarios without beamforming. It further elucidates how MRT contributes to contextual beamforming. The importance of localization in implementing contextual beamforming is also examined. Additionally, the paper delves into the use of …
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