Machine learning based optimization for vehicle-to-infrastructure communications
Journal Publication ResearchOnline@JCUAbstract
In this paper, we study wireless communications in vehicle-to-infrastructure communications. In certain situations, multiple vehicles within a local range need to exchange information via common roadside infrastructure. Example scenarios include busy intersections, and a driver with the knowledge of information from other vehicles can make safer decisions. Fast and reliable communications are essential in such use cases. We consider two different system models in this paper. In the first model, we consider the case where both the base station and vehicles are equipped with a single antenna. In the second model, we discuss the case where multiple antennas are installed on both the base station and vehicles. We show how the system can be optimized in both cases. We then discuss how machine learning can be adopted in both models to realize the optimized system performance. (C) 2018 Elsevier B.V. All rights reserved.
Journal
Future Generation Computer Systems
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Volume
94
ISBN/ISSN
0167-739X
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Pages Count
8
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Publisher
Elsevier
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EISSN
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DOI
10.1016/j.future.2018.10.047