An Overview of Mobility Management mechanisms and its challenges in 5G and Beyond networks

Ensuring a seamless connection during the mobility of various User Equipments (UEs) is one of the significant challenges facing the generations of wireless systems. However, enabling the high-band spectrum such as millimeter Wave (mmWave) which is also one of the important key factors of 5G networks, to deal with the increasing network capacity demands and provide high coverage to users. Therefore, a new cell deployment (small cells) with short ranges to operate by the mmWave is required to serve the need appended to the macro-cells which are responsible to operate long-range radio waves. The small cell deployment leads to develop a new network structure called Heterogeneous Networks (HetNets). As a result, the number of passthrough cells by using the handover (HO) process will be dramatically increased. Mobility Management (MM) in such massive network deployment will become crucial especially when it comes to very high mobility speed users. The MM solutions render them ineffective as they will not be able to provide the required reliability, flexibility, and scalability. Thus, smart algorithms and techniques are required in future networks. Also, machine learning (ML) techniques are well capable to support 5G latest technologies that are expected to deliver high data rates to upcoming use cases and services such as massive machine type communications (mMTC), enhanced mobile broadband (eMBB), and ultra-reliable low latency communications (uRLLC). This paper aims to provide an inclusive review of the MM in 5G HetNet and the involvement of AI mechanisms and techniques in terms of connected mode MM schemes. Besides, this paper addresses the challenges and suggests possible solutions for the 5G networks and beyond.