Communications Engineering Department lecturer publishes a research at the Istanbul Conference (IEEE) DeSE2023

Professor Dr. Thamer Muhammad Jameel, a lecturer in the Department of Communications Engineering, published a research entitled:

Performance Evaluation of SISO-OFDM Channel Equalization Utilizing Deep Learning

in: 16th International Conference on Developments in eSystems Engineering (DeSE), Istanbul, Turkey, 2023

The goal of the research is to use the channel equalizer based on deep learning (DL) for orthogonal frequency division multiplexing (OFDM) communication systems and to take advantage of neural networks to mitigate the effects of channel weakness and improve the performance of the OFDM system. The primary goal of this research is to evaluate the performance of the adopted channel equalizer. On deep learning in order to address the shortcomings of the ZF and MMSE equations in terms of modulation order, number of pilots and course prefix (CP).

Simulation results show that the DL-based channel equalizer can outperform the MMSE equalizer when the number of pilots increases, with or without CP, for both low- and high-frequency selective channel models, respectively. The results also demonstrate how deep learning of CNN structures can be used in a SISO OFDM system to enhance channel equalization.

Numerical evidence also showed that deep learning significantly reduced channel equalizer errors compared to traditional methods.