Game theoretic framework for future generation networks modelling and optimization

A new cost efficient automated planning and optimization method is proposed for OFDMA future-generation cellular networks targeting throughput maximization. The mathematical formulation is a non-linear multi-objective optimization problem subject to minimum interference, cost and similar resource constraints at each cell within a defined heterogeneous traffic environment. The fundamental objective is to maximize the individual cell throughput without deteriorating it over other cells, which results in a throughput equilibrium maximization over multiple cells. This implicitly implies traffic and co-channel interference congestion avoidance across the network whilst maintaining both cost efficiency and quality of service (QoS) policies. Optimal solution existence is subject to the network size, traffic and computational complexity constraints which converges to a throughput equilibrium or alternatively to the well known Nash Equilibrium (NE).