Assistant Lecturer Wala’a Hussein, in the Department of Chemical Engineering and Oil Refining at the College of Oil and Gas Engineering, Assistant Walaa Hussein, published a scientific research paper in the International Journal of INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING entitled "Super-Resolution Channel Estimation based on Deep Learning in Reconfigurable Intelligent Surface Systems"
This research elucidates the application of deep learning (DL) for communication channel estimation. It employs a two-dimensional visualization to represent the time-frequency attributes of a rapidly fading communication channel. A cascaded channel with large dimensions and complex statistics is used in a RIS-aided multi-user multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) communication system The research also involved designing a deep learning model called SRIR-ChNet. The channel uses an SR system paired with a noise-reducing IR system.
