5G-REMOTE
5G Realzeitkommunikation für das "Taktile Internet“
Laufzeit 2021 -
This project explores the profound importance and applications of antenna beamforming technology, especially in the dynamic landscape of 5G and emerging 6G wireless communication systems. We use the beamforming technique, which involves strategically adjusting the spacing and phases of antennas in an array to control the direction and shape of the wireless signal beam. This manipulation results in improved signal quality and a noticeable reduction in errors. The project's core aim is to fine-tune beamforming parameters, such as antenna placement and beam steering angles, using advanced ray-tracing techniques for accurate predictions of signal strength and coverage outdoors and indoors by using optimization methods and machine learning algorithms. In optimization, we try to optimize the total channel capacity by identifying the ideal beam configurations for each transmitter and receiver. To address the complexities of determining optimal angles, the project employs various optimization methods to enhance efficiency. Furthermore, the project explores the integration of machine learning methodologies, specifically reinforcement learning, to predict optimal antenna configurations. Machine learning plays a crucial role in improving network efficiency and accuracy, particularly in situations requiring real-time processing. Therefore, the thematic core revolves around the imperativeness of meticulous modeling, optimization strategies, and the seamless integration of machine learning paradigms to propel the evolution of efficient, dependable, and pioneering wireless communication technologies.
Link zur DFG-Seite: https://gepris.dfg.de/gepris/projekt/457407152