Abstract :
Random access has been widely studied in literature, but its time dynamics remains a pretty open research problem at this time, particularly for cognitive radio networks that are operating most in transient status but being investigated usually in steady-state. Modifying prey-predator model, we therefore consider radio resources as preys and users as predators to dynamically understand the network system behavior. We start from exploring ALOHA, then include the sensing mechanism into the scenario. Furthermore, we incorporate partially or randomly connected graph to practically represent realistic interactions among users and resources. By modeling sensing errors and delay, for the first time, the time dynamics of a cognitive radio network can be fully characterized, and consequently random access operating conditions can be practically understood and specified for network engineering design.
