Zone-Based Load Balancing in LTE Self-Optimizing Networks: A Game-Theoretic Approach

Abstract

Mobility load balancing (MLB) is an important use case in long-term evaluation (LTE) self-optimizing networks (SONs). To combat the potential ping-pong load transfer and low-convergence issues, we propose a game-theoretic solution to the SON MLB to solve the asymmetry traffic distribution among multiple cells and the potential hidden-cell case. The proposed algorithm, which is referred to as zone-based mobility load balancing (ZLB), optimally redistributes the load of all cells within a zone. We model the multiple cells' ZLB as a Cournot game, where multiple cell pairs carry out load balancing (LB) simultaneously under the constraints of load distribution of hidden cells. Simulation results show that the ZLB algorithm can overcome the ping-pong LB problem and that the convergence time of LB is also dramatically reduced. Meanwhile, the load distribution of ZLB is more balancing than that of MLB, and the performance of average blocking probability and the number of unsatisfied users of ZLB are significantly improved.