Mobility Prediction Based Resource Management

Abstract

Owing to the challenging nature of emerging applications, such as augmented reality, 4 K video streaming, and remote surgery, 5G networks are expected to deal with a broad range of issues including higher data rate provision, less energy consumption, lower latency, etc. Therefore, intelligent and proactive network management is envisioned to be an integral part of 5G in order to make the communication networks more agile, dynamic, and efficient. In this regard, mobility prediction has gained a significant amount of attention owing to their diverse application domains. This article focuses on discussing the implementation of mobility prediction for resource management in mobile communication networks. After describing the challenges expected from 5G networks with related statistical facts, predictive mobility management is introduced with its distinctive applications. After that, the use of mobility prediction in communication networks is elaborated according to different resource types, such as radio, energy, and built‐in resources, and the corresponding state‐of‐the‐art literature is classified accordingly.

The Role of Artificial Intelligence Driven 5G Networks in COVID-19 Outbreak: Opportunities, Challenges, and Future Outlook

“…However, with existing networks, these connections will be prone to frequent disruptions arising from insufficient support for high mobility broadband services. Improved mobility management (Imran et al, 2019a;Ozturk et al, 2019;Tabassum et al, 2019) and proactive handover (HO) optimization techniques (Ahmed and Alzahrani, 2019;Mollel et al, 2019;Mollel et al, 2020) are required for consistent quality of service along highways or speed train routes.…”

“…Mobility predictions indeed have been identified as a valid and strong tool to manage resources in cellular networks in terms of radio, in-built (e.g., processing power, memory, etc. ), energy, etc., as discussed in Imran et al (2019a). These schemes mainly try to predict future HOs of users in order to perform some of the aforementioned HO steps prior to the occurrence of the HO so that the HO signaling cost can be reduced.…”