Tag Anti-collision Algorithm for RFID in Underdetermined States Based on Local Sparse Constraints

For when the number of identification tags is greater than the number of readers, the underdetermined blind separation algorithm separation effect is poor and the RFID system reading speed is slow, this paper proposes a tag anti-collision algorithm for RFID in underdetermined state based on L2,1 norm and local sparse constraints. To obtain sparse encoding of RFID signals, the algorithm introduces local coordinate constraints so that each data point is represented as a linear combination of several anchor points in the vicinity, and to maintain the local structure of the data, only a few anchor points close to the data point are used to represent the data in order to obtain local geometric similarity properties. Adding L2,1 parametric regularization to the coefficient matrix can induce many rows in V to decrement to zero, while selecting important non-zero features and discarding unimportant ones, thus effectively achieving sparse coding of the source signal with the reconstruction of local geometric properties. The results of simulation showed that in the underdetermined state, the tag anti-collision algorithm for RFID in the underdetermined state based on local sparse constraints proposed in this paper can obtain a more effective signal blind separation effect, which makes the throughput of RFID system greatly improved.