US 12,328,208 B2
Machine learning based channel estimation method for frequency-selective MIMO system
Asmaa Abdallah, Thuwal (SA); Abdulkadir Çelik, Thuwal (SA); Ahmed Eltawil, Irvine, CA (US); and Mohammad Mansour, Beirut (LB)
Assigned to KING ABDULLAH UNIVERSITY OF SCIENCE AND TECHNOLOGY, Thuwal (SA)
Filed by KING ABDULLAH UNIVERSITY OF SCIENCE AND TECHNOLOGY, Thuwal (SA)
Filed on Feb. 14, 2023, as Appl. No. 18/168,876.
Claims priority of provisional application 63/311,247, filed on Feb. 17, 2022.
Prior Publication US 2023/0300006 A1, Sep. 21, 2023
Int. Cl. H04L 25/02 (2006.01); H04B 7/0413 (2017.01)
CPC H04L 25/0242 (2013.01) [H04B 7/0413 (2013.01); H04L 25/0254 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A machine learning based method for channel estimation for a multiple-input multiple-output (MIMO) system, the method comprising:
receiving a measured signal y[k] at a receiver of the MIMO system;
finding subcarriers k of the measured signal y[k];
estimating, with a convolutional neural network (CNN) channel amplitudes, channel amplitudes ĝ[k] of the measured signal y[k];
reconstructing a channel Ĥ[k][k], between the receiver and a transmitter of the MIMO system, based on the estimated channel amplitudes ĝ[k] and a low resolution whiten measurement matrix custom characterW; and
adjusting a parameter of the MIMO system based on the reconstructed channel Ĥ[k][k],
wherein the channel amplitudes ĝ[k] are simultaneously estimated by the CNN.