The safety of vulnerable road users is paramount, particularly as we move towards the widespread adoption of autonomous and self-driving vehicles. In this study, we investigate the use of a six-element distributed antenna system (DAS), operating at 5.8 GHz and mounted on the exterior (i.e., roof and wing mirrors) of an automobile, to enhance signal reliability for pedestrian-to-vehicle (P2V) communications. Due to its low complexity and ease of implementation, we consider the use of switch-and-examine combining with post-examining selection (SECps) scheme to combine the signal received by the DAS. During our experiments, a pedestrian wearing a wireless device on their chest either stood stationary or walked by the side of a road. It was found that the overall signal reliability depends on not only the number, but also different groupings of the antennas which are selected. The goodness-of-t results have shown that the temporal behavior of the diversity gain was adequately described by the Gaussian distribution. Building upon this, we also provide some useful insights into the antenna selection through the comparison of three different antenna selection mechanisms, namely per-sample random antenna selection, one-shot antenna selection and per-sample optimal antenna selection.
|Journal||IEEE Transactions on Vehicular Technology|
|Early online date||05 Aug 2021|
|Publication status||Early online date - 05 Aug 2021|
Bibliographical notePublisher Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
- Antenna measurements
- Antenna selection
- distributed antenna system
- diversity gain
- Diversity methods
- Diversity reception
- Legged locomotion
- pedestrian-to-vehicle communications
- switched combining
ASJC Scopus subject areas
- Automotive Engineering
- Aerospace Engineering
- Electrical and Electronic Engineering
- Applied Mathematics
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Mobile communications channels involving people and vehiclesAuthor: Doone, M., Dec 2022
Supervisor: Morales, D. (Supervisor) & Cotton, S. (Supervisor)
Student thesis: Doctoral Thesis › Doctor of PhilosophyFile