End-to-end Learning for OFDM: From Neural Receivers to Pilotless Communication

11 September 2020

Papers citing "End-to-end Learning for OFDM: From Neural Receivers to Pilotless Communication"

5 / 5 papers shown

Title
Transformers are Provably Optimal In-context Estimators for Wireless Communications Vishnu Teja Kunde Vicram Rajagopalan Chandra Shekhara Kaushik Valmeekam Krishna R. Narayanan S. Shakkottai D. Kalathil J. Chamberland 87 5 0 01 Nov 2023
Pruning the Pilots: Deep Learning-Based Pilot Design and Channel Estimation for MIMO-OFDM Systems Mahdi Boloursaz Mashhadi Deniz Gunduz 51 124 0 21 Jun 2020
DeepRx: Fully Convolutional Deep Learning Receiver Mikko Honkala D. Korpi Janne M. J. Huttunen 79 134 0 04 May 2020
Deep Learning-Based Communication Over the Air Sebastian Dörner Sebastian Cammerer J. Hoydis S. Brink 45 710 0 11 Jul 2017
An Introduction to Deep Learning for the Physical Layer Tim O'Shea J. Hoydis AI4CE 128 2,188 0 02 Feb 2017