Interactions Study of Self Optimizing Schemes in LTE Femtocell Networks
El-murtadi Suleiman, Kais
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One of the enabling technologies for Long Term Evolution (LTE) deployments is the femtocell technology. By having femtocells deployed indoors and closer to the user, high data rate services can be provided efficiently. These femtocells are expected to be depolyed in large numbers which raises many technical challenges including the handover management. In fact, managing handovers in femtocell environments, with the conventional manual adjustment techniques, is almost impossible to keep pace with in such a rapidly growing femtocell environment. Therefore, doing this automatically by implementing Self Organizing Network (SON) use cases becomes a necessity rather than an option. However, having multiple SON use cases operating simultaneously with a shared objective could cause them to interact either negatively or positively. In both cases, designing a suitable coordination policy is critical in solving negative conflicts and building upon positive benefits. In this work, we focus on studying the interactions between three self optimization use cases aiming at improving the overall handover procedure in LTE femtocell networks. These self optimization use cases are handover, Call Admission Control (CAC) and load balancing. We develop a comprehensive, unified LTE compliant evaluation environment. This environment is extendable to other radio access technologies including LTE-Advanced (LTE-A), and can also be used to study other SON use cases. Various recommendations made by main bodies in the area of femtocells are considered including the Small Cell Forum, the Next Generation Mobile Networks (NGMN) alliance and the 3rd Generation Partnership Project (3GPP). Additionally, traffic sources are simulated in compliance with these recommendations and evaluation methodologies. We study the interaction between three representative handover related self optimization schemes. We start by testing these schemes separately, in order to make sure that they meet their individual goals, and then their mutual interactions when operating simultaneously. Based on these experiments, we recommend several guidelines that can help mobile network operators and researchers in designing better coordination policies.