Patent ID: 11882460
Assignee: ROBERT BOSCH GMBH
Field: Digital communication (Electrical engineering)
Classification: CPC H  G | IPC G  H

Claim 11:
12. A method for training a deep neural network (GEN), wherein the method comprises:
providing (202) at least one training set (ts), wherein the at least one training set ts) comprises a low-resolution QoS map (lrM2) associated with a radio communications network (RCN2), a high-resolution QoS map (hrM2) associated with the radio communications network (RCN2), and environment information (ei2) characterizing the environment (E2) of the radio communications network (RCN2);
propagating (204) input data comprising the low-resolution QoS map (lrM2) and the environment information (ei2) through the deep neural network (GEN), wherein the input data is provided as input parameter in an input section of the deep neural network (GEN), and wherein in an output section of the deep neural network (GEN) at least one neural network based high-resolution QoS prediction map (hrPM2) is provided;
determining (206) a comparison (c) by comparing the neural network based high-resolution QoS prediction map (hrPM2) and the high-resolution QoS map (hrM2) of the training set (ts); and
training (208) the deep neural network (GEN) with the training set (ts) in dependence of the comparison (c).