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With a focus on channel coding, we develop a variety of encoding and decoding algorithms designed to improve error-rate performances, including the construction of low-density parity-check (LDPC) codes, and the decoding algorithms for 5G polar codes, etc. We also investigate coded MIMO and massive MIMO systems. Multiple techniques have been devised that bring about considerable improvement for the entire communication system. In addition, we design good algorithms for use in channel decoders and MIMO detectors and are suitable for integrated circuit (IC) implementation in modern 5G/B5G communication systems.
ICs are the foundation of electronic products such as mobile phones and computers. The IC design group focuses on the VLSI designs for channel codecs (e.g. LDPC and Polar codecs) and MIMO transceivers for 5G/B5G systems. Communication algorithms and VLSI architectures are designed concurrently in order to optimize the chip performance. The associated training enables students to become professional IC designers who have the ability to both develop advanced hardware architecture and build a chip. Graduates will have a tremendous opportunity to join a leading IC design house such as MediaTek, Realtek, Silicon Motion, or Phison, etc.
Machine learning is a thriving field of electrical engineering and computer science that allows the computer to learn the structures of data without needing to be explicitly programmed. Many impressive applications have been identified in the field of machine learning, including image recognition, and artificial intelligence (AI), etc. Numerous projects relating to these fields are currently in progress in our lab. For example, machine-learning-aided decoding, which combines machine learning and channel coding to further improve the performance of traditional channel coding. Furthermore, one of our research projects, FinTech, includes time-series prediction functionality related to currencies and the stock market, etc.