Year: 2014
Type: conference-paper
Abstract: Superposition codes are efficient for the additive white gaussian noise channel. We provide here a replica analysis of the performances of these codes for large signals. We also consider a Bayesian approximate message passing decoder based on a belief-propagation approach, and discuss its performance using the density evolution technic. Our main findings are 1) for the sizes we can access, the message-passing decoder outperforms other decoders studied in the literature 2) its performance is limited by a sharp phase transition and 3) while these codes reach capacity as B (a crucial parameter in the code) increases, the performance of the message passing decoder worsen as the phase transition goes to lower rates.
Authors: Jean Barbier, Florent Krzakala
Institution: École Normale Supérieure - PSL
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2088934832