Consensus based power control algorithms for heterogeneous networks

The resource allocation problem is crucial for unveiling the potential of heterogeneous networks. The demand for higher data rates from an increasing number of devices compels the operators to look for solutions beyond the traditional network architecture. Heterogeneous network architecture is a promising solution to provide data rates required by the emerging applications and high-speed multimedia services. In this dissertation, we focus on the interference management for heterogeneous networks which is a major problem to be resolved and propose solutions based on power control techniques. We utilize the inherent advantages of consensus algorithms such as non-essentially of objective functions and fairness to design power control algorithms suitable for the task of resource allocation in heterogeneous networks. In this dissertation, several novel, distributed and self optimized power adjustment algorithms are proposed. Contrary to the approaches in the literature, the instantaneous or statistical measurements on channel gains are not required during the power adjustment process. The convergence analyses reveal that the proposed algorithms achieve optimum solution for the power allocation problem with fairness constraints, even under a setup with imperfect communication links. Furthermore, the theoretical analyses show that the convergence properties of the proposed algorithms are preserved under different spectrum allocation schemes. The numerical analyses are in agreement with the theoretical analyses and demonstrate significant improvement in terms of overall network performance.