Neural Radio in DS-UWB IoT Applications

摘要

The paper presents a concept of direct sequence ultrawideband (DS-UWB) impulse radio receiver based on a physical neural network. Here is a theoretical grounding for radio signal processing with a deep learning mathematical model that has a hardware implementation. It is proposed to change the traditional way of radio signal processing and use a single neural network instead of a matched filter, a magnitude amplifier and a FPGA processor. The advantages of this solution in communication and remote sensing problems of IoT are discussed. The architecture of physical neural network was designed with an attention to ultrawideband short pulse (UWB-SP) radio signal behaviour in near and far radiation zones. The applicability of the neural radio concept is proved by simulation of AWGN communication channel for multiuser environment and real time RX signal processing by the designed neural network.