Inter-cell interference coordination in OFDMA networks: Two autonomous-distributed algorithms

In OFDMA cellular networks, inter-cell interference hinders system performance, especially for users located at the cell edges. Inter-cell interference coordination (ICIC) techniques have been investigated by both the academia and standardization communities to reduce the impact of interference and improve system performance. We first survey conventional frequency planning schemes, and classify ICIC schemes in terms of their distributivity and dynamicity. We highlight the advantages and disadvantages of these schemes using examples from the literature. We then evaluate the performances of frequency planning schemes, in particular, reuse-1, reuse-3, strict fractional frequency reuse (FFR) and soft frequency reuse (SFR). We compare their performances under different resource scheduling strategies via simulations. Based on the simulation results, we outline the design trade-offs for ICIC techniques to be used in OFDMA networks. The novel contribution of this thesis is the proposition of two autonomous-distributed ICIC algorithms. One is a dynamic algorithm based on game theory, where the base stations play a trial and error game to maximize the overall network throughput. The other is a semi-static algorithm based on cell-based measurements and aggregate feedback, whose goal is to increase the number of supportable users by optimizing FFR parameters. We evaluate the performance of the proposed algorithms against static ICIC schemes, via system simulations under a variety of scenarios. While the game-theoretic algorithm shows robust results, outperforming all static schemes under different conditions, we argue its suitability for implementation. Although the semi-static algorithm is open to implementation and still shows promising results, we indicate cases where its performance falls slightly under reuse-1. Finally, we discuss possible ways to improve our algorithms and we suggest future research directions.