The next-generation wireless networks are evolving into very complex systems because of the very diversified service requirements, heterogeneity in applications, devices, and networks.
Traditional networking approaches, i.e., reactive, centrally-managed, one-sizefits-all approaches, and conventional data analysis tools that have limited capability (space and time) are not competent anymore and cannot satisfy and serve that future complex networks regarding operation and optimization cost effectively.
Operators have been optimizing their networks all along, but even today, the prevailing approach is to independently optimize single key performance indicators (KPIs), or an element within the network independently.
--- ChatGPT The next-generation wireless networks are evolving into very complex systems. In order to optimize the performance of these networks, a more holistic approach is needed, which takes into account the interdependence between different network elements and the diverse requirements of different applications and services.
One possible approach to achieve this is through the use of machine learning (ML) and artificial intelligence (AI) techniques. ML algorithms can learn from data and observations, and can be used to identify patterns and make predictions. This can enable the network to adapt and optimize itself in real-time, based on changing conditions and demands.
AI techniques, such as deep learning, can also be used to analyze large amounts of network data and extract meaningful insights that traditional data analysis tools may miss. This can help network operators to identify potential issues and proactively address them before they become major problems.
In addition, the use of ML and AI can help to reduce the operational and optimization costs of next-generation wireless networks by automating certain tasks, such as network configuration and maintenance. This can free up network operators to focus on more complex and high-level tasks, such as strategic planning and network design.
Overall, the use of ML and AI techniques is becoming increasingly important for the effective operation and optimization of next-generation wireless networks. As these networks continue to evolve and become more complex, network operators will need to embrace these technologies in order to stay competitive and meet the diverse demands of their customers.
Reference List
- Kibria, M. G., Nguyen, K., Villardi, G. P., Zhao, O., Ishizu, K., & Kojima, F. (2018). Big data analytics, machine learning, and artificial intelligence in next-generation wireless networks. IEEE access, 6, 32328-32338.