TY - JOUR
T1 - Mobility and Handover Management in 5G/6G Networks
T2 - Challenges, Innovations, and Sustainable Solutions
AU - Saoud, Bilal
AU - Shayea, Ibraheem
AU - Alnakhli, Mohammad Ahmed
AU - Mohamad, Hafizal
N1 - Publisher Copyright:
© 2025 by the authors.
PY - 2025/8
Y1 - 2025/8
N2 - Compared to 4G long-term evolution (LTE) networks, 5G and 6G networks provide fast data transmission with little delay, larger base station capacity, enhanced quality of service (QoS), and extensive multiple-input-multiple-output (MIMO) channels. Nevertheless, the attainment of mobility and handover (HO) in 5/6G networks has been hindered by substantial changes in intelligent devices and the high-definition applications of multimedia. Therefore, the existing cellular network is compared with difficulties in transmitting large amounts of data at a faster rate, ensuring high QoS, minimizing latency, and efficiently managing HOs and mobility. This paper primarily addresses the difficulties related to HO and mobility management in 5G/6G networks. The findings of this paper emphasize the importance of aligning mobility and HO strategies with sustainable development goals to reduce energy consumption and improve resource allocation. It focuses on integrating innovative technologies such as artificial intelligence and machine learning to enhance the sustainability and efficiency of mobility and HO management. The paper provides a comprehensive analysis of the current body of the literature and explores essential metrics for measuring performance (known as KPIs) and potential solutions for difficulties linked to HO and mobility. The analysis takes into account established standards in the field. Furthermore, it assesses the effectiveness of existing models in dealing with HO and mobility management problems, considering criteria such as energy efficiency, dependability, latency, and scalability. This survey concludes by highlighting key challenges associated with HO and mobility management in existing research models. It also offers comprehensive assessments of the proposed solutions, accompanied by suggestions for future research.
AB - Compared to 4G long-term evolution (LTE) networks, 5G and 6G networks provide fast data transmission with little delay, larger base station capacity, enhanced quality of service (QoS), and extensive multiple-input-multiple-output (MIMO) channels. Nevertheless, the attainment of mobility and handover (HO) in 5/6G networks has been hindered by substantial changes in intelligent devices and the high-definition applications of multimedia. Therefore, the existing cellular network is compared with difficulties in transmitting large amounts of data at a faster rate, ensuring high QoS, minimizing latency, and efficiently managing HOs and mobility. This paper primarily addresses the difficulties related to HO and mobility management in 5G/6G networks. The findings of this paper emphasize the importance of aligning mobility and HO strategies with sustainable development goals to reduce energy consumption and improve resource allocation. It focuses on integrating innovative technologies such as artificial intelligence and machine learning to enhance the sustainability and efficiency of mobility and HO management. The paper provides a comprehensive analysis of the current body of the literature and explores essential metrics for measuring performance (known as KPIs) and potential solutions for difficulties linked to HO and mobility. The analysis takes into account established standards in the field. Furthermore, it assesses the effectiveness of existing models in dealing with HO and mobility management problems, considering criteria such as energy efficiency, dependability, latency, and scalability. This survey concludes by highlighting key challenges associated with HO and mobility management in existing research models. It also offers comprehensive assessments of the proposed solutions, accompanied by suggestions for future research.
KW - 5G/6G networks
KW - HO
KW - HetNet
KW - ML
KW - green technology
KW - resource efficiency
UR - https://www.scopus.com/pages/publications/105014328804
U2 - 10.3390/technologies13080352
DO - 10.3390/technologies13080352
M3 - Review article
AN - SCOPUS:105014328804
SN - 2227-7080
VL - 13
JO - Technologies
JF - Technologies
IS - 8
M1 - 352
ER -