Small cells are introduced as one of the key technologies of the new generation (5G) mobile networks. Among the existing small cell technologies, femtocells drew more research attention from both industry and academia because of their unplanned installation and management by users. Femtocell technology is a promising solution for offoading high volume cellular data traffic to low-powered indoor base stations. However, coexistence of femtocells with macrocell networks introduces special challenges to mobility management. In this research, adaptive mobility management in femtocell networks is explored. The aim of this research is to provide seamless and secure mobility and offoading to mobile users in dierent femtocell networks. Past research on mobility management in femtocell networks only focused on avoiding unnecessary handoffs and handoff failures while ignoring some important and practical issues, e.g., the ad-hoc nature of femtocells and offoading issues. Moreover, the effects of heterogeneous spectrum on mobility management in cognitive radio femtocell networks are never addressed. Furthermore, the service migration and the radio and computation offoading issues due to users' mobility are not well investigated.In this research, six adaptive mobility management schemes are proposed to address these issues. First, two adaptive handoff decision algorithms are proposed for closed-access and open-access femtocell networks. Then, a secure target cell selection scheme is designed for femtocell networks. An analytical model is also proposed to analyze the total handoff signaling cost. Later, a power control scheme along with the detection sensitivity scheme and a mobility management scheme are proposed to address the issues of heterogeneous spectrum in cognitive radio femtocells. Last, a joint handoff and offoading decision algorithm is proposed to reduce the service migration rate and the radio network congestion. The proposed mobility management schemes in this research are endowed with the ability to adapt to the existing practical challenges. Therefore, this research will provide important insights on next-generation femtocell networks.
