US 12,231,938 B2
Configuring an artificial intelligence based framework
Ahmed Hindy, Aurora, IL (US); Ankit Bhamri, Röder,mark (DE); and Vijay Nangia, Woodridge, IL (US)
Assigned to Lenovo (Singapore) Pte. Ltd., New Tech Park, Singapore (SG)
Filed by Lenovo (Singapore) Pte. Ltd., New Tech Park (SG)
Filed on Dec. 14, 2021, as Appl. No. 17/550,686.
Prior Publication US 2023/0189031 A1, Jun. 15, 2023
Int. Cl. H04W 24/10 (2009.01); G06N 3/04 (2023.01)
CPC H04W 24/10 (2013.01) [G06N 3/04 (2013.01)] 19 Claims
OG exemplary drawing
 
1. A method of a user equipment (UE), the method comprising:
receiving an indication indicating an artificial intelligence based framework;
receiving configuration information corresponding to the artificial intelligence based framework, wherein the configuration information comprises at least two of:
a scheme corresponding to the artificial intelligence based framework, wherein the scheme comprises a convolutional neural network, a recurrent neural network, a modular neural network, or a combination thereof;
a regularization technique corresponding to the artificial intelligence based framework, wherein the regularization technique comprises a Lasso regression technique, a Ridge regression technique, a dropout technique, or a combination thereof;
a set of neural network based parameters corresponding to the artificial intelligence based framework comprising: a number of layers, a number of nodes per hidden layer, a number of input nodes, a number of output nodes, a maximum number of edges having a weight that can be reported, or a combination thereof; and
an activation function corresponding to the artificial intelligence based framework, wherein the activation function comprises a first sigmoid function, a second sigmoid function, a rectified linear unit, an arc tangent function, or a combination thereof; and
communicating an artificial intelligence report corresponding to the artificial intelligence based framework based on the configuration information, wherein the artificial intelligence report comprises a set of values corresponding to the configuration information, or an indication of a subset of a set of channel resources, or both, and wherein the artificial intelligence report comprises values corresponding to a set of neural network based parameters corresponding to the artificial intelligence based framework including: a number of inner layers, a number of hidden layers, a number of input nodes, a number of output nodes, a number of nodes per inner layer, a weight per edge between two nodes in consecutive layers, a bias per node, or a combination thereof.