Abstract
This paper proposes a novel graph-based multicell scheduling framework to efficiently mitigate downlink intercell interference in OFDMA-based small cell networks. We define a graph-based optimization framework based on interference condition between any two users in the network assuming they are served on similar resources. Furthermore, we prove that the proposed framework obtains a tight lower bound for conventional weighted sum-rate maximization problem in practical scenarios. Thereafter, we decompose the optimization problem into dynamic graph-partitioning-based subproblems across different subchannels and provide an optimal solution using branch-and-cut approach. Subsequently, due to high complexity of the solution, we propose heuristic algorithms that display near optimal performance. At the final stage, we apply cluster-based resource allocation per subchannel to find candidate users with maximum total weighted sum-rate. A case study on networked small cells is also presented with simulation results showing a significant improvement over the state-of-the-art multicell scheduling benchmarks in terms of outage probability as well as average cell throughput.