Mobility and load aware radio resource management in OFDMA femtocell networks


Abstract: Recent evolutions in mobile networks have led to increased resource demands, especially from indoor users. Although recent technologies such as LTE have an important role in providing higher capacity, indoor users are not satisfied adequately. Femtocell networks are one of the proposed solutions that support high data rates as well as better indoor coverage without imposing heavy costs to network providers. However, interference management is a challenging issue in femtocell networks, mainly due to dense and random deployment of femto access points (FAPs). Therefore, distinct radio resource management (RRM) methods are employed to ensure acceptable levels of call dropping/blocking probability and spectral efficiency. However, the mobility of mobile users is an important issue in resource management of femtocell networks that has not been considered adequately. In this paper, we propose an algorithm that predicts the resource requirements of FAPs regarding mobility of their users and allocates the resources to the FAPs based on an extended load-based RRM algorithm that prioritizes handoff calls to incoming calls. Simulation results illustrate that the proposed method has shown lower call dropping probability and higher spectral efficiency compared to the benchmark algorithms.

Keywords: Femtocell networks, resource allocation, mobility prediction

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