Sensor Aided Beamforming in Vehicular Environment

Tan, M. C. , Li, M., Abbasi, Q. H. and Imran, M. (2020) Sensor Aided Beamforming in Vehicular Environment. In: 5th International Conference on the UK-China Emerging Technologies (UCET 2020), Glasgow, UK, 20-21 Aug 2020, ISBN 9781728194882 (doi: 10.1109/UCET51115.2020.9205411)

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221490.pdf - Accepted Version



Sensor fusion is a well-known technique to harvest the raw data from various type of sensors and generate a more accurate prediction on certain operation parameters that helps to improve the accuracy and efficiency of a big system. Many industries have been benefited from the sensor fusion such as robotic, agriculture, healthcare, autonomous vehicle, navigation and so on. In the smart antenna industry, the conventional beamforming is implemented in the costly field programmable grid array (FPGA) platform with the complex direction of arrival (DOA) algorithm. In this work, we are presenting a feasibility study on a lower cost alternative called sensor aided beamforming that make use of the raw data from the existing sensors in the vehicle, combined with some simple mathematically calculation to determine the beam angle of the mobile client and roadside infrastructure. We have presented a practical approach to study the sensor aided beamforming system in the real environment by simulating the beamforming parameters for a moving vehicle moves along the road that was pre-installed with roadside access points (AP). The result has proofed that the sensor aided method can be used to realize the beamforming in the smart antenna system, with the IoT sensors cost approximately less than U20comparedwiththeFPGApricerangeofaroundU200, the sensor aided beamforming will be a cheaper and affordable alternative to the conventional beamforming system that usually realized with the complex direction of arrival algorithm and higher cost.

Item Type:Conference Proceedings
Glasgow Author(s) Enlighten ID:Abbasi, Dr Qammer and Imran, Professor Muhammad and Moh Chuan, Tan
Authors: Tan, M. C., Li, M., Abbasi, Q. H., and Imran, M.
College/School:College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
College of Science and Engineering > School of Engineering > Systems Power and Energy
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