This invention discloses a dual-mode communication method for the power
Internet of Things (IoT) based on
deep learning for channel
estimation, relating to the field of power IoT communication technology. The method includes: designing a unified
MAC layer protocol and setting a
bit error rate (BER) requirement factor field in the data frame structure; obtaining power line and low-power
wireless communication link parameters based on this, and determining the optimal communication path by introducing perturbation parameters;
processing the initial channel matrix using
deep learning to generate feature channel weights and perform residual connections, outputting
channel state information; dynamically adjusting the BER requirement factor using a gradient adjustment method and calculating the sub-
stream allocation ratio; and splitting the service data into sub-streams proportionally and transmitting them through corresponding links. This invention achieves intelligent selection of power IoT communication links and adaptive allocation of service data.