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

## TL;DR

This paper surveys the deep unfolding technique, which combines iterative algorithms with neural networks, highlighting its applications in communication systems like MIMO detection, precoding, and decoding, and discusses future research directions.

## Contribution

It provides a comprehensive overview of deep unfolding in communications and introduces new directions for applying this method to various communication tasks.

## Key findings

- Deep unfolding improves detection and decoding in MIMO systems.
- The method demonstrates versatility across multiple communication tasks.
- Open research problems are identified for future exploration.

## Abstract

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.