Underdetermined RFID Tag Anti-Collision Based on Bounded Component Analysis

Abstract

Radio Frequency Identification (RFID) is one of the key technologies of the Internet of Things. However, during its application, it faces a huge challenge of co-frequency interference cancellation, that is, the tag collision problem. The multi-tag anti-collision problem is modeled as a Blind Source Separation (BSS) problem from the perspective of system communication transmission layer signal processing. In order to reduce the cost of the reader antenna, this paper uses the boundedness of the tag communication signal to propose an underdetermined RFID tag anti-collision method based on Bounded Component Analysis (BCA). This algorithm converts the underdetermined tag into the signal collision model is combined with the BCA mechanism. Verification analysis was conducted using simulation data. The experimental results show that compared with the nonnegative matrix factorization (NMF) algorithm based on minimum correlation and minimum volume constraints, the bounded component analysis method proposed in this article can perform better. Solving the underdetermined collision problem greatly improves the effect of eliminating co-channel interference of tag signals, improves the system bit error rate performance, and reduces the complexity of the underdetermined model system.