Machine Learning and Artificial Intelligence in Next-Generation Wireless Network
It tackles the problem of inefficient resource utilization and service delivery for network operators and subscribers in future wireless systems, but it is incremental as it reviews existing technologies without introducing new methods.
This paper addresses the challenge of managing next-generation wireless networks, which are diverse and complex, by proposing the integration of machine learning, AI, and big data analytics to enhance capacity and effectiveness, concluding that these technologies are essential for making networks self-adaptive and proactive.
Due to the advancement in technologies, the next-generation wireless network will be very diverse, complicated, and according to the changed demands of the consumers. The current network operator methodologies and approaches are traditional and cannot help the next generation networks to utilize their resources most appropriately. The limited capability of the traditional tools will not allow the network providers to fulfill the demands of the network's subscribers in the future. Therefore, this paper will focus on machine learning, automation, artificial intelligence, and big data analytics for improving the capacity and effectiveness of next-generation wireless networks. The paper will discuss the role of these new technologies in improving the service and performance of the network providers in the future. The paper will find out that machine learning, big data analytics, and artificial intelligence will help in making the next-generation wireless network self-adaptive, self-aware, prescriptive, and proactive. At the end of the paper, it will be provided that future wireless network operators cannot work without shifting their operational framework to AI and machine learning technologies.