Implementation and Analysis of Reward Functions Under Different Traffic Models for Distributed DSA Systems

In this paper, we implement and analyze a resource allocation protocol for distributed dynamic spectrum allocation (DSA) systems. The DSA protocol is a learning-based protocol that allows secondary users (SU) to exploit the spectrum bands efficiently in a distributed manner without the need of information exchange. The implementation and test of the proposed protocol is done using ns3 assuming that the SUs selecting the same band share it in accordance with a carrier sense multiple access (CSMA) scheme. The evaluation of the proposed protocol is done under various traffic models. We show the importance of the objective function's choice; used as a utility to be maximized in the learning. We also show the impact of various practical aspects taken into consideration while implementing the protocol on the system's achieved performance.