End-to-End Learning of Communication Systems with Novel Data-Efficient IIR Channel Identification
Sprache des Titels:
Englisch
Original Buchtitel:
2023 57th Asilomar Conference on Signals, Systems, and Computers
Original Kurzfassung:
In this paper, we introduce a novel end-to-end deep
learning procedure for communication systems, which is data-
efficient and capable of dealing with infinite memory length
of communication channels. Therefore, as opposed to recent
works, we utilize a low-complexity algorithm 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 the auto-encoder neural network. We study the performance
of the algorithm for a variety of challenging channels from
different domains of communication engineering showing the
broad applicability of the proposed approach.
Forschungs-