US 12,349,002 B2
Deep learning-based wireless communication synchronization structures
Faycal Ait Aoudia, Saint-Cloud (FR); Jakob Hoydis, Paris (FR); Sebastian Cammerer, Tuebingen (DE); Matthijs Jules Van Keirsbilck, Berlin (DE); and Alexander Keller, Berlin (DE)
Assigned to Nvidia Corp., Santa Clara, CA (US)
Filed by NVIDIA Corp., Santa Clara, CA (US)
Filed on Mar. 24, 2023, as Appl. No. 18/189,565.
Claims priority of provisional application 63/342,766, filed on May 17, 2022.
Prior Publication US 2023/0379746 A1, Nov. 23, 2023
Int. Cl. H04W 28/02 (2009.01); H04B 1/713 (2011.01); H04W 74/0833 (2024.01)
CPC H04W 28/0226 (2013.01) [H04B 1/713 (2013.01); H04W 74/0833 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system comprising:
a preprocessor to transform a received wireless signal in the form of a resource grid for a plurality of user equipment devices into a matrix of symbol group features for a narrowband physical random-access channel;
a neural network configured to transform the symbol groups from the preprocessor into predictions of active user equipment devices;
a first twin neural network comprising:
a first neural sub-network to transform the symbol groups from the preprocessor into time-of-arrival predictions for signals from the user equipment devices; and
a second neural sub-network to transform the symbol groups from the preprocessor into carrier frequency offset predictions for signals from the user equipment devices.