A Channel Cognitive Method For Wireless Fading Channel Using Variable-Length Markov Chain

Compared with the traditional wireless communication design which is based on a central infrastructure, the basic idea of cognitive radio are mainly the user-centered and goal-driven. Therefore, through the research on the dynamic propagation characteristics and fast adaptation from the cognitive terminals, the sensing capacity in local dynamic wireless environment of those terminals can be improved, that is very helpful to the research on the kernel theory and technology of Cognitive Radio.A new cognitive method for fading characteristics in the local wireless channel from the cognitive terminals is proposed in this paper. This method takes VLMC (Variable-Length Markov Chain) technology to characterize the fading channel, extract the statistical characteristics and predict the future states of the local dynamic wireless environment.The main contribution and innovation of this paper are as follows:1. Based on the received data, a model that optimally represents a fading channel with VLMC is proposed. This model consists of two main components:1) the optimal fading partition under the constraint of a transmission policy and2) the derivation of the best VLMC representation. The VLMC modeling based on the prior knowledge is also described.2. A statistic computing method of local fading channel characteristics is derived. The statistical characteristics treated by VLMC are mapped to local dynamic fading channel parameters to explore the fading characteristics under different wireless environments further.3. On a basis of learning and recognizing the statistic characteristics of the VLMC model, the future fading states of the channel parameters are predicted.4. The simulation is carried out to evaluate the performance of the proposed cognitive method. The results demonstrate that the cognitive method using VLMC can provide an optimal tradeoff between accuracy and complexity.