Learning to Communicate: Channel Auto-encoders, Domain Specific Regularizers, and Attention

Autor:	O'Shea, Timothy J, Karra, Kiran, Clancy, T. Charles
Rok vydání:	2016
Předmět:	Computer Science - Learning Computer Science - Information Theory Computer Science - Networking and Internet Architecture
Druh dokumentu:	Working Paper
Popis:	We address the problem of learning efficient and adaptive ways to communicate binary information over an impaired channel. We treat the problem as reconstruction optimization through impairment layers in a channel autoencoder and introduce several new domain-specific regularizing layers to emulate common channel impairments. We also apply a radio transformer network based attention model on the input of the decoder to help recover canonical signal representations. We demonstrate some promising initial capacity results from this architecture and address several remaining challenges before such a system could become practical.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1608.06409 Zobrazit plný text záznamu View this record from Arxiv