Deep Unfolding for Communications Systems: A Survey and Some New Directions

Deep unfolding is a method of growing popularity that fuses iterative optimization algorithms with tools from neural networks to efficiently solve a range of tasks in machine learning, signal and image processing, and communication systems. This survey summarizes the principle of deep unfolding and discusses its recent use for communication systems with focus on detection and precoding in multi-antenna (MIMO) wireless systems and belief propagation decoding of error-correcting codes. To showcase the efficacy and generality of deep unfolding, we describe a range of other tasks relevant to communication systems that can be solved using this emerging paradigm. We conclude the survey by outlining a list of open research problems and future research directions.

Published in:
Proceedings Of The 2019 Ieee International Workshop On Signal Processing Systems (Sips 2019), 266-271
Presented at:
33rd IEEE International Workshop on Signal Processing Systems (IEEE SiPS), Nanjing, PEOPLES R CHINA, Oct 20-23, 2019
Jan 01 2019
New York, IEEE

 Record created 2020-08-20, last modified 2020-10-29

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