A light-weight machine learning framework is established for intelligent adaptation among multiple fingerprints to find a near-optimal BS association and beam ...
To meet the above challenges, we develop a light-weight learning framework for BS association and beam alignment in mmWave vehicular systems. The main ...
The idea of trajectory-aware fingerprint is proposed, which extracts the combined effect of mobility, propagation environment, and blockages so as to ...
In this paper, we discuss various ways of incorporating machine learning techniques in the area of dynamic spectrum access, especially in vehicle communications ...
Exploiting the vacant spectrum resource at mmWave bands provides the potential for fulfilling the requirements of broadband services.
In this paper, we propose fast machine learning (FML), which is a low-complexity and a highly scalable online learning algorithm for mmWave base stations.
Apr 16, 2024 · Location information coupled with machine learning (ML) beam recommendation is one way to reduce the overhead of beam pair selection. In this ...
Feb 2, 2023 · A first step towards the ML-optimized end-to-end wire- less communication networks is to analyze the performance of these approaches on the ...
Apr 27, 2018 · Next, we propose a lightweight context-aware on- line learning algorithm, namely FML, with proven performance bound and guaranteed convergence.
Enabling Machine Learning based Cooperative Perception with ...
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Sep 28, 2024 · The main research objective of this project is to understand the sensing and communication challenges to achieving cooperative perception among ...