Performance Optimization Of RFID Communication And Its Application In Indoor Positioning

With the rapid development of the wireless sensor technology and mobile Internet technology,the information service based on the location-awareness become more and more popular,which has shown infinite vitality in many fields such as indoor navigation,security monitoring and information transmission.Among them,the appropriate positioning sensor,the accurate and stable positioning algorithm is the premise and key to realize the whole indoor location information service.However,the existing indoor positioning technology has some disadvantages,for example,the high cost of the system,poor portability of the positioning sensor,small data storage capacity and poor stability of the algorithm,which has restricted the popularization of location-aware information service.The indoor positioning technology based on the Radio Frequency Identification(RFID)and machine learning have provided a new path for the field of location-aware services,which has many advantages such as low cost,easy to use,and the better stability of positioning algorithmIn this paper,the Bit Error Rate(BER)of RFID communication system and location-aware service were studied.Firstly,according to the bit error rate of Ultra High Frequency(UHF)RFID communication system,the convolutional code error correction coding theory is adopted,and the corresponding solution is put forward,which can effectively reduce the BER and improve the reliability of UHF RFID communication system.On the other hand,in view of the problem of positioning accuracy and the stability of the algorithm,the intelligent machine learning and heuristic algorithm are integrated into the indoor positioning,and the corresponding optimization scheme is proposed Finally,the feasibility and superiority of the proposed scheme is proved by comparing the performance of the algorithm and the experimental results,and the main work and innovation of the paper are as follows(1)The problem of data transmission BER is analyzed from the angle of improving the communication reliability of the UHF RFID system,and a corresponding method to reduce the BER of the UHF RFID communication system is proposedThe UHF RFID system is easy to be interfered in the long distance communication,the system reliability is reduced.Therefore,in this paper,the convolutional code is introduced into the communication coding of the system,and the corresponding simulation model of the anti-interference ability based on the UHF RFID channel coding is constructed.The simulation results show that compared with the cyclic code,the convolutional code can be used to reduce the BER and improve the real-time performance of the communication system in UHF RFID communication coding,furthermore,the(2,1,7)convolutional code is more suitable for UHF RFID communication coding(2)By combining the machine learning theory,a RFID indoor positioning algorithm based on Support Vector Machine(SVM)is proposedThe focus of the current research is to improve the accuracy and the stability of the positioning algorithm.Therefore,in this paper,the SVM algorithm is integrated into the indoor positioning,and a RFID indoor positioning model based on the SVM is established Furthermore,by combining the Received Signal Strength Indication(RSSI)between the reader and the tag,the positioning model is used to predict the location of the target tag The experimental results show that the proposed method has higher positioning accuracy and more stable performance than the other commonly used methods(3)According to the idea of the heuristic algorithms,a RFID indoor positioning algorithm based on Particle Swarm Optimization(PSO)optimized SVM is proposedThe positioning accuracy of the algorithm is directly affected by the SVM model parameters in the SVM positioning algorithm,and the performance of the positioning algorithm can be further improved by the combination of the optimal SVM model parameters.Therefore,in this paper,an optimization algorithm is proposed,which integrates the heuristic algorithm into the machine learning positioning model.Namely,the optimal parameters of SVM positioning model are obtained by using the PSO algorithm with superior searching ability,and the RFID location prediction model based on PSO optimized SVM(PSO-SVM)is constructed.The experimental results show that the optimal positioning model parameters can be obtained by PSO algorithm,and the positioning accuracy and stability of the algorithm are further improved.