Residual Cigarette Recycle System Spectrum Switching Based on Markov Model

Abstract

In the process of communication of residual cigarette recycle system, due to the residual cigarette recycling bin WIFI switch with the signal strength, signal quality, distance of WIFI and other reasons. In order to keep the residual cigarette recycling bin in a non-inductive switching state, WIFI needs to adopt seamless Switching technology [1]. In which cognitive radio automatic networking (CRAN) is one of the core technologies, in order to suppress cognitive users from interfering with authorized users, it is necessary to reduce WIFI switching times as much as possible. Advance a cognitive wireless dynamic WIFI switching method based on detection of the WIFI chanel idle time (PWCIT). The theory is based on a known-state sequence hidden Markov [2] model (KSS-HMM). The selection method of the alternative WIFI is given, and the optimal channel is selected for data transmission by comparing the date transmission throughput of each candidate WIFI. The simulation results show that compared with the traditional channel selection method and the random channel [3] selection, the method can significantly reduce the number of WIFI handovers and improve the throughput of cognitive [4] users.