A Game Theory based Approach for Opportunistic Channel Access in Green Cognitive Radio Networks
Akanksha Srivastava, Mani Shekhar Gupta, Gurjit Kaur · 2019
Green cognitive radio network (GCRN) is an emerging technology which offers an auspicious solution to alleviate spectrum scarcity and energy-saving problem in 5G by proper utilization of unused network resources. In this work, we represent a game-theory based stochastic solution for distributed channel selection problem when secondary users' (SU) statistics and the total number of available channels are unknown. In game theory to attain Nash equilibrium points (NEP) is difficult due to insufficient information about channel availability and secondary users. Initially, we suggest a channel selection algorithm to attain the NE points with the assumption that perfect environment information is known. On the basis of this we represented the relation between the number of SUs with system throughput. A novel opportunistic channel access (OCA) algorithm based on stochastic automata is investigated which neither requires the information about the number of SUs and channel availability. To overcome the problem of data collision and for enhancement of spectrum capacity of wireless system OCA is a significant solution which works on traffic load balancing of SUs among several networks. OCA is a modern spectrum management concept developed to manage and organize access to available channels and promote energy efficient communication.