Research On Capture Effect For RFID Tag Anti-collision Algorithm

Radio frequency identification is based on the principle of electromagnetic induction. It can automatically identify lots of tags in a short time without visualization, wire and high capable of environment. In recent years, as the rapid development of the Internet of things(IOT) industry, RFID is given more attention which is the key technology to IOT. However with logistics, warehousing and other industries the development of RFID technology in the practical application, there are some problems to solve which are low tag recognition rate and slow standardized setting progress. Especially when lots of tags are needed to identify in a short period of time, it will cause tags collision problem by tags signal interference between the response data and reduce the throughput of the system.The thesis studies tag anti-collision algorithm based on Dynamic Frame Slot Aloha(DFSA) and aims at tag number estimation algorithm, frame length coefficient setting method and optimization identification cycle, etc. Research the influence of capture effect on system performance, and improve the existing collision algorithm. The main content includes:Analyze the improved collision principle which is based on DFSA and estimate the number of tags by Vogt. Adopt fast frame length adjustment method which is combined bit-slot time slot with continuous collision time slot detection. Then give a frame length setting coefficient under different time slot factor and a method for frame length adjustment cycle optimization control.Focus on the influence of capture effect to DFSA with SIR model, an improved tags estimation method based on Chebyshev and a novel Capture Effect Optimization Grouping algorithm(CEOG) is proposed by ISO18000-6 Type C. The high-level tags are first identified by CEOG which can reduce the impact of capture effect to RFID system. By the theory analyzing and simulations, system throughput is improved more efficient than CMEBE by CEOG.