A game-based power optimization for 5G femtocell networks

Spectrum sharing deployment of femtocells brings interferences which dramatically degrade network performance. Hence, interference control is a crucial challenge for femtocell networks. In this paper, we propose a power optimization approach for 5G femtocell networks consisting of macrocell and underlying femtocells to manage the interference. Firstly, we formulate the problem based on a non-cooperative game to analyze the competition among the users to access shared spectrum. We then design a pricing mechanism in the utility function to guarantee quality of service (QoS) requirements of macro users. The mechanism lets the macro users experience lower interference and achieve the minimum required data rate. As a result, QoS requirements of both macro and femto users are fulfilled in a non-cooperative manner. We also design a minimax decision rule to optimize the worst-case performance and find an optimal transmission power for each user. By adjusting the optimal power for each user, the maximum aggregate interference is minimized, and the network throughput is maximized. Finally, we develop an iterative learning-based algorithm to implement the proposed scheme and achieve the game equilibrium. Theoretical analysis and simulation results verifies the effectiveness of the proposed mechanism in terms of throughput maximization, QoS assurance and interference mitigation.