English

Machine Learning Algorithm for NLOS Millimeter Wave in 5G V2X Communication

Networking and Internet Architecture 2020-12-23 v1 Machine Learning

Abstract

The 5G vehicle-to-everything (V2X) communication for autonomous and semi-autonomous driving utilizes the wireless technology for communication and the Millimeter Wave bands are widely implemented in this kind of vehicular network application. The main purpose of this paper is to broadcast the messages from the mmWave Base Station to vehicles at LOS (Line-of-sight) and NLOS (Non-LOS). Relay using Machine Learning (RML) algorithm is formulated to train the mmBS for identifying the blockages within its coverage area and broadcast the messages to the vehicles at NLOS using a LOS nodes as a relay. The transmission of information is faster with higher throughput and it covers a wider bandwidth which is reused, therefore when performing machine learning within the coverage area of mmBS most of the vehicles in NLOS can be benefited. A unique method of relay mechanism combined with machine learning is proposed to communicate with mobile nodes at NLOS.

Keywords

Cite

@article{arxiv.2012.12123,
  title  = {Machine Learning Algorithm for NLOS Millimeter Wave in 5G V2X Communication},
  author = {Deepika Mohan and G. G. Md. Nawaz Ali and Peter Han Joo Chong},
  journal= {arXiv preprint arXiv:2012.12123},
  year   = {2020}
}

Comments

14 pages, 9 figures, conference 7th International conference on Computer Networks and Communications (CCNET 2020), AIRCC Publishing Corporation

R2 v1 2026-06-23T21:13:12.614Z