Dynamic Network Service Selection in Intelligent Reflecting Surface-Enabled Wireless Systems: Game Theory Approaches

In this paper, we address dynamic network selection problems of mobile users in an intelligent reflecting surface (IRS)-enabled wireless network. particular, the dynamically select different service providers (SPs) and services over time. The are composed adjustable resources IRS transmit power. To formulate SP selection, adopt evolutionary game which able to adapt their selections depending on utilities that they achieve. For this, replicator dynamics is used model adaptation users. allow take past experiences into account decisions, further enhanced version game, namely fractional study selection. incorporates memory effect captures users’ decisions. We theoretically prove both approaches have a unique equilibrium. Finally, provide numerical results demonstrate effectiveness our proposed approaches. reveal some important finding, for instance, with effect, can achieve utility higher than without effect.