Macrocell and small cell deployments and self-organizing network (SON) techniques work together to increase indoor cellular network capacity and ensure better quality of service (QoS). As a consequence of uneven local user densities and temporal or spatial fluctuations of traffic, the network may suffer overload situations, which partially degrades network performance. Load balancing self-optimization introduces automatic and intelligent mechanisms to tune network parameters in order to improve the overall cellular network performance. This paper proposes novel load balancing methods based on fuzzy logic controllers (FLC) that evaluate temporarily overloaded situations and resize cell coverage areas by an adaptive process of adjusting cell transmission power. To accomplish this goal, classical network indicators are analyzed (e.g., call blocking ratio, available radio resources) while a novel and simple, although powerful, indicator (not mentioned in the literature yet) is additionally proposed as the system input. This indicator is related to the maximum allowed number of users in a femtocell. The proposed methods have been evaluated and compared with the literature in a realistic scenario. Keywords Self-organizing networks Self-optimization Femtocell Indoor Load balancing Fuzzy logic controller
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