Intelligent Localization for Integrated Sensing and Communication: Machine Learning-Driven Approaches
Integrated Sensing and Communication (ISAC) systems. As 6G networks advance, the need for more efficient data collection, more intelligent system adaptability, and more accurate localization results. Traditional outdoor localization methods like GPS are limited indoors due to signal blockages, underscoring the need for innovative indoor localization technologies to meet the evolving requirements of modern applications.
This "Open Access" book addresses key challenges in indoor localization using Channel State Information (CSI) and machine learning. It covers three core aspects:
1. More Efficient CSI Collection: Reducing human intervention in the data collection process through automated methods while ensuring high-quality, reliable data.
2. More Intelligent CSI Updates: Developing adaptive mechanisms that allow for real-time updates of CSI values, ensuring system robustness and flexibility in dynamic environments.
3. More Accurate Localization Applications: Employing advanced machine learning algorithms to improve localization precision, even in complex indoor settings.
Through comprehensive theoretical insights and real-world experimental studies, this book presents the latest advancements in CSI-based indoor localization systems. The various machine learning techniques explored demonstrate their robustness and adaptability in real-world settings. Ideal for researchers, engineers, and students, this "Open Access" book provides both foundational and cutting-edge knowledge for anyone interested in developing intelligent indoor localization systems. Whether you're new to the field or an experienced professional, this "Open Access" book offers valuable insights for advancing localization technologies in the age of ISAC and 6G.
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