Channel State Information
Channel state information (CSI) describes the characteristics of a wireless communication channel, crucial for optimizing signal transmission and reception. Current research heavily focuses on improving CSI acquisition and utilization, particularly through machine learning techniques like deep learning (including recurrent neural networks, autoencoders, and transformers), and generative models to address challenges such as limited data, imperfect CSI, and high dimensionality. These advancements aim to enhance the performance of various wireless systems, including 5G and beyond, by improving spectral efficiency, reducing feedback overhead, and enabling new applications like wireless sensing and positioning. The impact spans both theoretical understanding of wireless channels and practical improvements in communication system design.
Papers
Multi-modal Image and Radio Frequency Fusion for Optimizing Vehicle Positioning
Ouwen Huan, Tao Luo, Mingzhe Chen
Multi-modal Data based Semi-Supervised Learning for Vehicle Positioning
Ouwen Huan, Yang Yang, Tao Luo, Mingzhe Chen
RSSI-Assisted CSI-Based Passenger Counting with Multiple Wi-Fi Receivers
Jingtao Guo, Wenhao Zhuang, Yuyi Mao, Ivan Wang-Hei Ho