机器学习能否帮助在5G中提供新的用例和场景?

Teodora Sandra Buda, H. Assem, Lei Xu, D. Raz, Udi Margolin, Elisha J. Rosensweig, D. López, M. Corici, M. Smirnov, R. Mullins, Olga Uryupina, A. Mozo, B. Rubio, Ángel Martín, A. Alloush, Pat O'Sullivan, I. B. Yahia
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引用次数: 32

摘要

5G代表着下一代通信网络和服务,将带来一系列新的用例和场景。反过来,这些将从网络和服务管理的角度解决一系列新的挑战,如网络流量和资源管理、大数据管理和能源效率。因此,需要新颖的技术和策略以更智能的方式应对这些挑战。在本文中,我们提出了当前网络和业务管理的局限性,并从管理的角度详细描述了5G预计面临的挑战。本文的主要贡献是提出了一组5G的用例和场景,其中机器学习可以帮助解决他们的管理挑战。预计机器学习可以为网络和应用提供更高、更智能的监控和管理水平,提高运营效率,促进未来5G网络的需求。
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Can machine learning aid in delivering new use cases and scenarios in 5G?
5G represents the next generation of communication networks and services, and will bring a new set of use cases and scenarios. These in turn will address a new set of challenges from the network and service management perspective, such as network traffic and resource management, big data management and energy efficiency. Consequently, novel techniques and strategies are required to address these challenges in a smarter way. In this paper, we present the limitations of the current network and service management and describe in detail the challenges that 5G is expected to face from a management perspective. The main contribution of this paper is presenting a set of use cases and scenarios of 5G in which machine learning can aid in addressing their management challenges. It is expected that machine learning can provide a higher and more intelligent level of monitoring and management of networks and applications, improve operational efficiencies and facilitate the requirements of the future 5G network.
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