Online spectrum allocation for cognitive cellular network supporting scalable demands

Abstract

We advocate an online spectrum allocation system for cognitive cellular network supporting scalable demands. Our system's demands processing model is online model, which means that allocation result is returned immediately. To solve the tough issues of online spectrum allocation, we try to balance the spectrum utilization and future coming demands. A state machine is introduced to allocate spectrum efficiently, and at different state system have different procedures to provide service to customers. To make good use of scalable property of demand and to increase fairness among customers, the concept of satisfaction degree is introduced. We also analyze our system's state and its transition theoretically and give the derivation of every parameter of system and the method to calculate them. Enough work is done to evaluate the system with real data evaluation and results show that the system is efficient and robust under different cases in which the customers' arrival rate and service time are varied.