Research Achievements
1.Implementing a Demapping Algorithm for ATSC 3.0 Receivers Using Machine Learning
Our laboratory focuses on applying machine learning to demapping in ATSC 3.0 receivers, leveraging model training to enhance performance and reduce bit error rate.
2.Genetic Algorithm for ATSC 3.0 Channel Estimation
Our laboratory investigates the application of genetic algorithms in DFT-based channel estimation for ATSC 3.0 receivers, utilizing genetic search to find suitable windows for channel impulse responses to further improve the channel estimation accuracy.
3.LTE-A
Our laboratory’s research covers LTE-A uplink and downlink transmission, focusing on the system architecture of the physical (PHY) layer and the medium access control (MAC) layer.
4.ATSC 3.0
Our laboratory’s research focuses on the ATSC 3.0 physical layer, including hierarchical multiplexing techniques, channel estimation, demapping, and encoding/decoding.