Big Data and 5G

A blog post for “Big Data Perspective and Challenges in Next Generation Networks” published in Future Internet (21 June 2018) — Full paper available at http://www.mdpi.com/1999-5903/10/7/56/htm

Summary

With the development towards the next generation cellular networks, i.e., 5G, the focus has shifted towards meeting the higher data rate requirements, potential of micro cells and millimeter wave spectrum. The goals for next generation networks are very high data rates, low latency and handling of big data. The achievement of these goals definitely require newer architecture designs, upgraded technologies with possible backward support, better security algorithms and intelligent decision making capability. In this survey, we identify the opportunities which can be provided by 5G networks and discuss the underlying challenges towards implementation and realization of the goals of 5G. This survey also provides a discussion on the recent developments made towards standardization, the architectures which may be potential candidates for deployment and the energy concerns in 5G networks. Finally, the paper presents a big data perspective and the potential of machine learning for optimization and decision making in 5G networks.

Keywords: 5G; data analysis; mobile communication; wireless communication

Open Issues

We briefly discuss some open issues. This also gives a direction on further advancements of studies at the crossroad of big data and 5G, as addressing these issues can give major breakthroughs.

Proactive caching and computing: Computing and caching cost for next generation networks can be minimized through modern big data analytics approaches. In this way, resources are to be efficiently distributed and utilized resulting in balancing the caching and computing overhead. For instance, the intermediate and final results should only be stored if meaningful, as storing all the information is costly.

Security and Privacy: Big data analytics uncovers the hidden information from within the huge data. Consequently, massive data analysis can cause security and privacy issues. During the storage, management and processing stages, data should be encrypted well, to assure that it cannot be manipulated or altered. Moreover, access to the data should be allowed for authorize entities only via secured channels. Thus, security and privacy issues are key concerns for such a massive data analysis and should be addressed intelligently.

Big Heterogeneous data: Big data sources are of different types with different data rate, mobility, and packet loss. The analysis of heterogeneous data in wireless networks is challenging. Heterogeneous data bring spatio-temporal dynamics. Thus, unconventional approaches are required for big spatio-temporal data analysis in mobile networks.

Remarks

The key technologies discussed include the ultra-dense networking, millimeter wave spectrum and massive MIMO. We identify the challenges which need to be overcome and the possible potential architecture design towards 5G implementation. We also outline the energy concern in 5G networks and find that it is always at the foremost of the challenges for 5G networks. During device design, service models are under consideration for 5G, and their backward compatibility will be of huge importance for both the users as well as for service providers. We also present a big data perspective on 5G and the opportunities that machine learning techniques have to offer for learning, inference and decision making on 5G data. There are even more domains in 5G networks which have not been covered in this text in detail, however, possess key importance. Security and privacy of the candidate architectures, hardware, and data transfer protocols in 5G networks pose major challenges and require further research. We hope that this survey will give readers a useful insight into the future generation networks and help the beginners to develop an understanding and realize the opportunities and challenges in 5G networks.