AFSOS: An Auction Framework and Stackelberg Game Oriented Optimal Network's Resource Selection Technique in Cognitive Radio Networks

The upcoming 5G and beyond wireless networking technologies are intended to coexist with different communication networks to solve the spectrum scarcity problem. The seamless roaming across integrated wireless networks and an optimal network's resource allocation would be a doable challenge for designing futuristic networks. The cognitive radio (CR) networks, with the inclusion of game theory, can handle spectrum scarcity issues by permitting spectrum access to the secondary user (SU) in the absence of a primary user (PU). This work proposes an AFSOS (an Auction Framework and Stackelberg game oriented Optimal network's resource Selection) technique to achieve a maximum payoff and acceptable interference power restraint in CR networks. The contest among candidate networks can be modeled as a Stackelberg game, and the contest between CR nodes and candidate networks can be modeled as an auction framework. As a schema for the realization and capabilities evaluations, the CR networks consisting of LTE cellular network interworking with Wi-Fi network for multiple access points (APs)/single vehicle (low traffic environment) is analyzed. This framework is further analyzed for single AP/multiple CR nodes (high traffic environment). The equilibrium for the Stackelberg game is achieved, and the proposed AFSOS technique is analyzed with numerical examples. The results show that the proposed AFSOS technique is more operative to obtain maximum payoff.