Written by IEEE | July 13, 2017 | Updated: December 9, 2017
The increased development of the internet and the mobile communication industry has caused more complex mobile networking systems causing increased traffic. These systems are called mobile heterogeneous networks (HetNets) and there are many challenges to running these networks successfully. One solution that stands out is using artificial intelligence techniques.
Since HetNets are expanding and evolving, researchers are trying to adapt different types of AI systems to aid them. AI techniques such as machine learning, bio-inspired algorithms and fuzzy neural networks, ant colony optimization, as well as Markov and Bayesian models could help improve the smartness, efficiency and performance of these large-scale HetNets.
Incorporating AI practices to HetNet management can ultimately boost mobile service performance. AI could also diminish the need for human involvement in running the networks, optimize network capacity, self configure and update, self-heal any failures in the system, and self-optimize to improve performance.
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Recently, mobile networking systems have been designed with more complexity of infrastructure and higher diversity of associated [...]