IOT-Based Injection-Locked Microwave Photonic Frequency Division Signal Processing

Abstract

When building an injection-locked microwave photonic frequency division signal processing model for the Internet of Things, the waveform and frequency of the microwave have an important impact on its performance. How to optimize and adjust the injection-locked microwave photonic frequency division signal processing effect needs more research and exploration. Taking the traditional mode architecture as a reference, this paper constructs an injection-locked microwave photonic frequency division signal processing model based on the Internet of Things. In this paper, the popular deep analysis method is used to optimize the model, and the photonic technology is matched with the microwave analysis. The purpose of this construction is to weaken the microwave integration error and improve the calculation accuracy to a higher level. In addition, aiming at the difficult problem of microwave signal generation, this paper uses the optical injection method to lock the microwave photons and generate waveform signals, which makes the model data more representative, so as to solve the problems of unstable microwave signals and high transmission costs. This paper also discusses the possibility of microwave photon filtering and frequency division signal processing of microwaves. The optimal solution is determined by analyzing the experimental results of various technical means, thus proving that the injection-locked microwave photonic frequency division signal processing means has better stability and a higher fitting degree.