SC390 - Introduction to Forward Error Correction
Sunday, 06 March
13:00 - 17:00
Short Course Level: Beginner
Georg Böcherer; Huawei Technologies; Technical University of Munich, Germany
Short Course Description:
Error-control coding, the technique of adding redundancy in controlled fashion to transmitted data so as to correct errors introduced by noise or other channel impairments, is a key component of modern optical communication systems. This course introduces basic concepts in coding and information theory: channel models and channel capacity (the Shannon limit), encoders and decoders (hard-decision and soft-decision), linear block codes, code rate and overhead, Hamming distance, net coding gain, generator matrices, parity-check matrices, and syndromes. Specific families and constructions of error-correcting codes will be described, including single parity check-, Reed-Muller-, Hamming-, Reed-Solomon-, and BCH codes. An overview of FEC codes used in optical communications will be given.
Short Course Benefits:
This course should enable participants to:
Define the key parameters of an error-correcting code.
Explain the system-level benefits provided by FEC.
Discuss the existence of fundamental limits (Shannon capacity) on FEC.
Interpret generator-matrix and parity-check-matrix descriptions of a code.
Encode and decode a binary Hamming code.
Describe the key parameters of Reed Solomon codes and binary BCH codes.
Interpret the properties of FEC codes used in optical communications.
Short Course Audience:
Systems engineers, system operators and managers who need to understand the costs and benefits in applying physical-layer error-control coding in a communications link. No previous background in information theory or algebra is assumed.
Georg Böcherer holds M.Sc. (ETH Zürich, 2007), Ph.D. (RWTH Aachen University, 2012), and Dr.-Ing. habil. (Technical University of Munich (TUM), 2017) degrees, all in electrical engineering. 2017-2020, he worked as senior engineer at the Optical Communication Technology Lab of Huawei Technologies France, and since 2020, we works as principal engineer at the Optical and Quantum Communications Lab of Huawei Technologies Germany. Since 2018, he is lecturer at the TUM. His research is on machine learning, forward error correction, DSP, and information theory. G. Böcherer is the inventor of Probabilistic Amplitude Shaping. He received a Bell Labs Prize in 2015, the Johann-Philipp-Reis-Preis in 2017 and the 2019 IEEE/OSA JLT best paper award in 2019.