End-to-End Learning of Communication Systems with Novel Data-Efficient IIR Channel Identification

Description

In this work, a novel end-to-end deep learning procedure for communication systems is introduced, which is data efficient and capable of dealing with infinite memory length of communication channels. Therefore, as opposed to recent works, a low-complexity algorithm is utilized to identify the communication channel. The channel model is obtained purely from data and its output is differentiable with respect to its input, which is a basic requirement for gradient-based optimization of an auto-encoder neural network implementing an end-to-end optimized communication system. The performance of the algorithm is studied for a variety of challenging channels from different domains of communication engineering showing the broad applicability of the proposed approach.

Period	30 Oct 2023
Event title	Asilomar Conference on Signals, Systems and Computers (ACSSC 2023)
Event type	Conference
Location	United StatesShow on map