Research On Optimization Of M-ary Backscatter Technology For Passive Sensing System

The Internet of Things,as an extension of the information system to the physical world,has greatly expanded people's ability of recognizing and controlling the physical world.Passive sensing system,as the connection engine of the Internet of Things,is profoundly changing people's living environment and lifestyle.The number of active IoT devices will have reached 26 billion by 2020,and the average annual compound growth rate will exceed 35%.When the number of IoT micro-devices is gradually increasing and the volume of passive low-power devices is gradually reduced,the challenges faced by passive sensing systems will be more severe.The most important feature of passive sensing systems is the use of backscatter technology,so as to achieve wireless energy harvesting and passive sensing communication.In actual application,the system is affected by factors like energy limitation,link loss and complex environmental signals.The data transmission rate directly affects the throughput performance of the entire system.Therefore,in passive and low-power modes,how to improve the communication status between IoT devices and improve the overall data transmission efficiency of the system is more important.This thesis focuses on improving the data exchange efficiency of passive sensing systems.The main work is as follows:(1)Based on the ambient backscatter technology,this thesis proposes and adopts a scalable high-order backscatter modulation technique to improve the data transmission rate of passive sensing systems.By refining the reflection state to obtain a faster data transmission rate,the reflection channel has higher capacity and frequency band utilization.It is verified by experiments that the high-order backscatter modulation scheme can fundamentally and effectively improve the data transmission rate of the system.In this thesis while improving the overall throughput performance of the system,it is repaired and optimized in the face of the problem that the label is in the process of label communication and the decoding is difficult.The practical problem of improving the throughput performance of the passive communication system in the system design at the expense of the bit error rate is solved.(2)Based on the basic principle of ambient backscatter,a multi-level signal energy estimation model based on optimal ML(Maximum Likelihood(ML)signal detection is established.Through the detection and estimation of the reflected signal,the different reflection states of the label are discriminated,the discriminant problem is abstracted into a mathematical model,and the optimal multi-level energy detection threshold is derived by the closed SER calculation.For the ambient backscatter high-order modulation signal,the threshold value of the adjustment threshold is optimized,and the recognition efficiency of the system is improved while ensuring the improvement of the transmission rate.Finally,the system error rate is analyzed and compared under different channel conditions and experimental settings.The data throughput rate is nearly 60% higher than that of the original system under the experimental scene setting,which proves the feasibility of the backscatter optimization scheme proposed in this thesis.Compared with traditional back-scatter technology,the data transmission rate and system stability are improved.It shows that highorder M-PSK reflection modulation can achieve good communication performance between low-power passive sensing devices without using high-power and high-complexity devices and technologies.