Optimal Radio access in femtocell networks : a Bayesian approach

Femtocell networks offer a series of benefits with respect to conventional cellular networks such as better frequency reuse, improved coverage, higher data rates and extended battery life. However, a potential massive deployment of femto-access points (FAPs) poses a big challenge in terms of Radio Resource Management (RRM), which requires proper radio resource allocation techniques. Differently from macro base stations, FAP’s are typically installed by the subscribers and maintained without global planning, with no special consideration about traffic demands or interference with other cells, either femto or macro cells. Hence, a dense deployment of FAP’s might induce an intolerable interference to macro users or to other femto users. Having that in mind, in this work we develop several algorithms under the common root of the “Bayesian” approach. First, assuming static femto-to-femto interference we establish local coordinating schemes between FAP’s in order to maximize a network social welfare (or conversely, to minimize a social cost). Then, once having incorporated a model for the macro interferers’ activity, we extend such schemes in the time-frequency domain. On the latter case we start considering a single FAP accessing the radio channel in the presence of a dynamical interference environment. Then, with the support of Game Theory (GT), we extend the formulation to a multi-FAP scenario where nearby FAP’s react to the strategies of the other FAP’s, still within a dynamical interference scenario. The multi-user case is first approached using a strategic non-cooperative game formulation. Then we propose a coordination game based on the introduction of a pricing mechanism that exploits the backhaul link to enable the exchange of parameters (prices) among FAP’s. The numerical simulations show the worthiness of the joint effect of local coordination and interference estimation.