Heterogeneous wireless network traffic load estimation based on chaos theory

With the rapid development of high-speed wireless communication technology, more novel and different wireless networks are emerging. The co-existence of multiple wireless networks has made the wireless network environment complex and heterogeneous. Traffic flow characteristics study and effective traffic prediction algorithm selection are very important for optimal allocation of network resources, network protocol design and improvement of service quality in this heterogeneous wireless network. This paper uses non-statistical method which is based on chaos theory to make analysis of heterogeneous wireless network traffic flow characteristics. On that basis, a traffic model which uses phase space reconstruction algorithm on multivariate traffic time series is proposed and used for traffic prediction. Simulation results show that the proposed traffic prediction model can achieve better prediction performance.