Research On Signal Detection Technology Under Non-Ideal Conditions Of Bistatic Backscatter Communication Hardware

With the continuous development of the Internet of Things,backscatter communication can use external excitation source signals to complete the transmission of its own information,because of its low cost,low power consumption,wide deployment and other characteristics,more and more attention,laying the foundation for the realization of green Internet low-power communication.Due to the complex fading channel and direct link signal interference,it is difficult for the receiver to directly separate the received direct link and reflected link mixed signals,and it is difficult to detect the backscatter label symbol information.Therefore,the detection technology design of the receiver is one of the important problems in the backscatter communication system.The traditional backscatter communication system does not take into account the frequency offset phenomenon that may occur in the actual hardware system,so the receiver can not accurately complete the signal synchronization recognition and carrier synchronization.Based on the backscatter communication system model and receiver detection technology designed in the existing literature,this thesis is devoted to realizing signal detection in the backscatter communication system for multiple users and in the scene with the presence of the same frequency interference.Besides,considering the influence of the hardware non-ideal factors on the system,the corresponding frequency estimation algorithm is given for different frequency migration phenomena.In this thesis,the problem of signal detection of various backscatter communication systems is studied,and a backscatter system model based on single antenna code division multiple access is designed.In view of the scene where multiple devices are connected to detect symbol information at the same time,the code division multiple access method is used for signal coding and transmission,and the signal detection method using energy detection and maximum likelihood detection is designed.In this thesis,a system model based on multi-antenna interference suppression combined with backscattering is designed.The receiver regards the information of non-special backscattering tags as interference information,and a detection algorithm based on maximum ratio combination and multiple interference suppression combination is designed.At the same time,a sparse self-coding detection algorithm based on deep neural network is designed according to the characteristics of the label signal carried by the received information.The simulation results show that the backscattering system designed in this thesis can effectively estimate the channel and suppress the interference signal,and realize the detection of the label signal.At the same time,the influence of frequency migration caused by hardware nonideal factors on the detection performance of backscatter communication system is studied.Aiming at the influence of Sampling Frequency Offset(SFO)phenomenon on signal sampling,a timing error detection algorithm using Gardner timing synchronization circuit is designed.Aiming at the effect of Carrier Frequency Offset(CFO)phenomenon on signal phase and amplitude,a time-domain estimation algorithm using pilot training is designed.The simulation results show that the frequency estimation algorithm designed in this thesis can effectively calculate the frequency offset value generated by the system and complete the compensation of the system detection performance,and verify the effectiveness of the estimation algorithm.