Channel Quality

Channel quality, encompassing signal strength and reliability across various communication mediums, is a critical factor influencing the performance of numerous systems. Current research focuses on improving channel prediction and mitigation techniques, employing diverse approaches such as deep learning models (e.g., autoencoders, convolutional neural networks, recurrent neural networks) and attention mechanisms to enhance feature extraction and model efficiency. These advancements are significant for optimizing wireless communication, improving image and video processing (e.g., low-light enhancement, demoireing), and enhancing the accuracy of applications in diverse fields like medical image analysis, agriculture, and even cyber security threat detection.