Current Research Trends Machine Learning in 5G: A Bibliometric Analysis

Abstract

Researchers are attracted to emerging field 5G with machine learning. Many review articles have been carried out to analyze in a different direction of 5G with machine learning. However, no researcher presented bibliometric analysis on machine learning in the 5G research field to a detailed analysis of research status and future trend network in this research area. A bibliometric analysis was done in the current study using the bibliometric R tool and VOS viewer software. The relevant literature was collected period 2001 to 2021 from the Web of Science (WoS) Core Collection and Scopus database. The quantitative analysis was done in terms of a yearly published article, most trend research topic, and future direction in ML in 5G technology. Finally, the result indicated that China, the U.S.A., and India are the top countries to publish this field because China, the U.S.A., and the U.K. are the most cited countries. Beijing University of Posts and Telecommunications is the most relevant organization, Wang most appropriate and most influential author in this research area (5G in AI/ML). IEEE Access, IEEE transactions on vehicular technology, and Sensor are the most relevant journal. The main challenges in this field are low latency communication, resource allocation, resource management spectral efficiency, millimeter wave, 5G with the Internet of things (IoT), a device to device communication, power control, and massive MIMO. Deep learning, machine learning, cognitive radio, and reinforcement learning are artificial intelligence techniques used in 5G.