Dynamic Model for Network Selection in Next Generation HetNets With Memory-Affecting Rational Users

Recently, due to the staggering growth of wireless data traffic, heterogeneous networks have drawn tremendous attention capabilities enhancing capacity/coverage and reducing energy consumption for next generation networks. In this paper, we study a long-run user-centric network selection problem in 5G network, where strategies users can be investigated dynamically. Unlike conventional studies on model, incorporate memory effect consider fact that decision-making is affected by their memory, i.e., past service experience. Namely, select based not only instantaneous achievable experience but also within memory. Specifically, model interaction among framework fractional evolutionary game classical theory concept power-law We analytically prove equilibrium exists, unique uniformly stable. numerically demonstrate stability equilibrium. Extensive simulations been conducted evaluate performance game. The numerical results revealed some insightful findings. For example, user with positive achieve higher cumulative utility compared negative effect. Moreover, reduce loss user's caused small-scale fading.