Research On Access Selection And Congestion Control In Cognitive Networks

Since the concept of cognitive networks was first proposed at IEEE International Symposium on DySPAN 2005, there has been launched with great enthusiasm for research on the cognitive network. However, the current exploration of the cognitive network is still in its infancy phase, the preliminary framework of cognitive network system are still under explored. In this paper, we propose a Cognitive Network approach to solve the problem of the Wireless Network Access and congestion control.Under the concept of cognitive network framework, this paper studies the problem of wireless access. A information processing framework was proposed based on Fuzzy Logic which enables the implementation of a cognition process which is both cross-layer and network-aware; furthermore, we developed the cognitive function by realizing a more complete and reliable characterization of the performance of the whole network with the cognitive information from different devices. Subsequently, we defined a network access scheme based on Fuzzy Decision Making which allows each user to choose the Access Point that best satisfies its QoS requirements.Cognitive network congestion control technologies were discussed and main related problems were pointed out. The further research trend of cognitive network congestion control was presented. With exponential weighted by ARMA models to design a smooth function of RTT, a congestion control algorithm called CNFAST TCP is elaborated in detail. It improves the smooth estimation of round-trip delay and eliminates the fluctuations of the queue throughput and queuing delay. We studied the stability margin of the network parameters on system stability. Through quantitative analysis and performance evaluation methods on the congestion control algorithms, including fairness, stability and convergence, the comprehensive performance of the high-performance transmission system is systematically analyzed.