Channel State Information Feedback

Channel state information (CSI) feedback, crucial for efficient communication in advanced wireless systems like massive MIMO, aims to minimize the overhead of transmitting channel information from receiver to transmitter while maintaining accuracy. Current research heavily utilizes deep learning, employing architectures like autoencoders, recurrent neural networks (RNNs, such as BiLSTMs), and variational autoencoders (VAEs), often incorporating techniques like vector quantization and model-driven approaches to improve compression and reconstruction efficiency. These advancements are significant because they enable more spectrally efficient and reliable communication in high-dimensional MIMO systems, impacting both theoretical understanding and practical deployment of next-generation wireless technologies.