Throughput Maximization in Cognitive Radio System With Transmission Probability Scheduling and Traffic Pattern Prediction
In this paper, the authors propose a novel Transmission Probability Scheduling (TPS) scheme for opportunistic spectrum access based cognitive radio system, in which Secondary User (SU) aims to maximize its throughput when the collision probability perceived by Primary User (PU) is constrained under required threshold. Particularly, they first study the maximum achievable SU throughput when distribution of the PU idle period is known and the spectrum sensing is perfect. When the spectrum sensing is imperfect, they thoroughly quantify the impact of sensing errors on the SU performance. Furthermore, when the traffic pattern of the PU and its parameters are unknown, they propose a predictor based on Hidden Markov Model (HMM) to predict the future PU state.