Game Model for Dynamic Cell Association of Macro-User in Two-Tier Cellular Networks

Macro-small cells networks, which include a multiple small cells under the macro cell area, provide an attractive solution for meeting capacity requirements of the network and achieve higher user data rate transmission. The deployment of small cells also is an effective approach to reuse the spectrum that provide an increasing spatial reuse of bandwidth. In this study, we propose a game model to manage the macro user association in the heterogeneous network architecture composed of one single macro base station and a set of small-cells operating in the same spectrum. We construct an utility gain framework to allow macro base station to encourage macro users to play the same strategy (defined as a recommended small base station that offers a high throughput to the macro user with low interference, because the macro base station is considered as a controller of the current users under different small base stations) in order to help them to get an acceptable throughput. We obtain the best distribution of macro users equipment among small-cells and macro base station. The proposed game model is done in the dynamic and randomly environment. We use the Combined fully distributed payoff and strategy learning algorithm to prove in one side the existence of Nash equilibrium and to accelerate the convergence in the other side.