Stackelberg Game Theory for Rectifying Mutual Interferences among Secondary Users of Cognitive Radio Network in Comparison with Cournot Game Theory

Abstract

Aim: The aim of the study is to solve the problem of mutual interference among SUs based on Stackelberg game theory. Materials and Methods: This paper proposes an innovative algorithm based on Stackelberg game theory to reduce interference among secondary users. MATLAB software is used to implement the algorithm. The algorithm is tested to find Signal to Interference noise ratio (SINR) of about 10 secondary users in CRN using novel Stackelberg game theory and compared with the SINR of Secondary users using Cournot game theory. Results: The Statistical analysis is done by performing Independent Variable test and T-test using SPSS software. The mean SINR is maximum for Stackelberg game theory (100.9±1 mdb), and the least SINR (13.11±1mdb) is seen for Cournot game theory. Conclusion: The algorithm based on Stackelberg game theory shows maximum SINR than the Cournot game theory. Since SINR is maximum Signal quality will be high and Interference will be less among the users due to which the network performance is improved.