	US 12,284,654 B2
	Deep-learning for distributed channel feedback and precoding
Wei Yu, Toronto (CA); Foad Sohrabi, Toronto (CA); Kareem Attiah Alboraie, Toronto (CA); and Mohammadhadi Baligh, Ottawa (CA)
Assigned to THE GOVERNING COUNCIL OF THE UNIVERSITY OF TORONTO, Toronto (CA); and HUAWEI TECHNOLOGIES CANADA CO., LTD., Ottawa (CA)
Filed by HUAWEI TECHNOLOGIES CANADA CO., LTD., Kanata (CA); and THE GOVERNING COUNCIL OF THE UNIVERSITY OF TORONTO, Toronto (CA)
Filed on Nov. 9, 2023, as Appl. No. 18/505,831.
Application 18/505,831 is a continuation of application No. 16/912,949, filed on Jun. 26, 2020, granted, now 11,832,259.
Prior Publication US 2024/0163880 A1, May 16, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. H04W 72/21 (2023.01); G06N 3/04 (2023.01); H04B 7/06 (2006.01); H04L 5/00 (2006.01); H04W 76/27 (2018.01)

CPC H04W 72/21 (2023.01) [G06N 3/04 (2013.01); H04B 7/0626 (2013.01); H04L 5/0048 (2013.01); H04W 76/27 (2018.02)]

20 Claims

1. A method comprising:

obtaining, by a first device, a set of distributions of channels and noise;

receiving, by the first device, an instruction from a second device, wherein the instruction includes a specification of a first deep neural network, and the specification of the first deep neural network includes an indication of a selected deep neural network from among a set of deep neural networks;

receiving, by the first device, a reference signal from the second device;

obtaining, by the first device, a feedback message by processing, using the first deep neural network, the set of distributions of channels and noise, and the received reference signal;

transmitting, by the first device, the feedback message to the second device; and

receiving, by the first device, a data signal, wherein the data signal has been subjected to a precoding matrix, wherein the precoding matrix has been derived, by the second device, using a second deep neural network that has received, as input, the feedback message and feedback messages from other devices.