Machine Learning for Resource Management in Cellular and IoT Networks: Potentials, Current Solutions, and Open Challenges

By Fatima Hussain, Syed Ali Hassan, Rasheed Hussain, Ekram Hossain. IEEE Communications Surveys and Tutorials, 2019

324 citations recorded by the source corpus.

Internet-of-Things (IoT) refers to a massively heterogeneous network formed through smart devices connected to the Internet. In the wake of disruptive IoT with a huge amount and variety of data, Machine Learning (ML) and Deep Learning (DL) mechanisms will play a pivotal role to bring intelligence to the IoT networks. Among other aspects, ML and DL can play an essential role in addressing the challenges of resource management in large-scale IoT networks. In this article, we conduct a systematic and in-depth survey of the ML- and DL-based resource management mechanisms in cellular wireless and IoT networks. We start with the challenges of resource management in cellular IoT and low-power IoT networks, review the traditional resource management mechanisms for IoT networks, and motivate the use of ML and DL techniques for resource management in these networks. Then, we provide a comprehensive survey of the existing ML- and DL-based resource management techniques in wireless IoT networks and the techniques specifically designed for HetNets, MIMO and D2D communications, and NOMA networks. To this end, we also identify the future research directions in using ML and DL for resource allocation and management in IoT networks.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/3d66e3e38a79363282de3af36c8ee602075f406e

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In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

A Survey of Rate-Optimal Power Domain NOMA With Enabling Technologies of Future Wireless Networks (2019, methodology): “In [318], applications of ML and DL are discussed to resource optimization problems in IoT and other cellular networks, including a brief description of the applications to NOMA systems.”
Empowering Things With Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things (2020, background): “resource management in IoT networks has become a topic of interest, with advanced deep learning technologies showing promising results [51].”
Survey on Network Slicing for Internet of Things Realization in 5G Networks (2021, methodology): “A comprehensive survey on resource management in cellular and IoT networks using ML techniques, was presented in [230].”
Enabling Massive IoT Toward 6G: A Comprehensive Survey (2021, background): “The authors of [26] provided a survey on different aspects of resource management in cellular and IoT networks that leverage machine learning techniques.”