DYNAMIC SPECTRUM ACCESS TECHNIQUE USING MARKOV CHAIN

Dynamic Spectrum Access (DSA) is the new paradigm to access the unused spectrum at a given time. When designated user arrived on its licensed spectrum, a user will be hopped to the new vacant spectrum band in the white space. A Markov Chain (MC)is a stochastic model describing a sequence of possible events in which the probability of each event depends only on the state attained in the previous event. In this paper, we considered the dynamic spectrum access as a Markov Chain. We correlated DSA and MC and analyzed MCs. We create two MCs using a matrix of observed transition count and convert it with transition probability matrix. Then we plotted the Eigen values of transition matrices on the complex plane. Also, we find the stationary distribution of MCs. This analysis helps us to determine the channel's behavior and help us to prioritize the channels for the better quality of access.