Theoretical-Analysis-Based Distributed Load Balancing over Dynamic Overlay Clustering

In multicell networks, unbalanced cell loading can lead to decreased system stability and reduced fairness among serviced users. In this paper, we propose theoretical-analysis-based distributed load balancing (DLB) over dynamic overlay clustering implemented over a multicell network. The proposed system is divided into two parts: DLB and overlay clustering. First, for DLB, we define the long-term expected load after deriving the long-term expected rate in terms of proportional fairness. We then introduce two algorithms: DLB for load dispersion and DLB for edge-rate enhancement (ERE). These algorithms operate in a distributed manner based on mathematical analyses and load balancing characteristics. Second, through overlay clustering, load balancing within each cluster is consecutively performed on neighboring clusters, which enables the algorithm to optimally approximate in a distributed manner. The simulation results show that approximately 90% of the near-optimal performance in terms of load variation and ERE can be achieved with low complexity by using the proposed schemes. In addition, we discuss aspects and tradeoffs of the load balancing system.