Modeling RFID signal distribution based on neural network combined with continuous ant colony optimization

Radio Frequency Identification (RFID) has been rapidly developing for recent years as a kind of near field wireless communication technology depending on radio frequence signal. Now there are widespread researches and applications about RFID. To make the distribution of tags’ position rational and efficient, it is significant to obtain the signal strength model around reader. This paper uses neural network method to model the RFID reflected signal strength distribution. To achieve a satisfied solution, a continuous Ant Colony Optimization algorithm that can overcome the defect of BP algorithm is combined with neural network. We discuss the mechanism of algorithm in detail. The simulation and the actual experiment results are shown to prove the good performance of this method.