Self-organization in femtocells: A game theoretic approach to mitigate the interference and enhance the macrocell performance

Abstract

Mobile operators are compelled to explore new ways to improve their coverage, boost their network capacity, and lower their capital and operating expenditures. To reach these goals, small-cells are underlain macrocells which automatically creates interference (SINR) and to avoid this, short range, low power and low-cost base station which are decentralized and self-organizing by enacting the concept of game theory is implemented. In this system co-tier and cross-tier interference of macrocells and femtocells occurs which is avoided and a minimum guaranteed signal to interference plus noise ratio (SINR) is guaranteed at the macrocell user equipment. Individual performance of each femtocell is increased drastically to provide a better service to macrocell. The reinforcement learning procedure used here is fully distributed as every small cell base station requires only an observation of its instantaneous performance which can be obtained from its user equipment. Furthermore, it is shown that the proposed mechanism always converges to an epsilon Nash equilibrium when all small cells share the same interest. Finally real time example of this process is explained to validate the theoretical findings, highlighting the utility functions through which the results are arrived.