In a dynamically changing spectrum environment, it is very important to consider the statistics of different users' spectrum access so as to achieve more efficient spectrum allocation. In this chapter, we study a primary-prioritized Markov approach for dynamic spectrum access through modeling the interactions between the primary and the secondary users as continuous-time Markov chains (CTMCs). Using the CTMC models, to compensate for the throughput degradation due to the interference among secondary users, we derive the optimal access probabilities for the secondary users, by which means the spectrum access of the secondary users is optimally coordinated and the spectrum dynamics clearly captured. Therefore, a good tradeoff between the spectrum efficiency and fairness can be achieved. The simulation results show that the primary-prioritized dynamic spectrum access approach under the criterion of proportional fairness achieves much higher throughput than do the CSMA-based random access approaches and the approach achieving max–min fairness. Moreover, it provides fair spectrum sharing among secondary users with only small performance degradation compared to the approach maximizing the overall average throughput.

Introduction

Efficiently and fairly sharing the spectrum among secondary users in order to fully utilize the limited spectrum resources is an important issue, especially when multiple dissimilar secondary users coexist in the same portion of the spectrum band. Although existing dynamic spectrum access schemes have successfully enhanced spectrum efficiency, most of them focus on spectrum allocation among secondary users in a static spectrum environment.