The Monthly Newsletter of IEEE Vehicular Technology Society—June 2022

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From the IEEE Transactions on Vehicular Technology
Radar Detection in Vehicular Networks
Gourab Ghatak, Sanket Kalamkar, and Yash Gupta

Full title—Radar Detection in Vehicular Networks: Fine-Grained Analysis and Optimal Channel Access

Automotive radar is a critical feature in advanced driver-assistance systems. It is important in enhancing vehicle safety by detecting the presence of other vehicles in the vicinity.

The performance of radar detection is, however, affected by the interference from radars of other vehicles as well as the variation in the target radar cross-section (RCS) due to varying physical features of the target vehicle. Considering such interference and random RCS, this work provides a fine-grained performance analysis of radar detection.

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Specifically, using stochastic geometry, we calculate the meta distribution of the signal-to-interference-and-noise ratio that permits the reliability analysis of radar detection at individual vehicles.

We also evaluate the delay aspect of radar detection, namely, the mean local delay which is the average number of transmission attempts needed until the first successful target detection.

Full Article: IEEE Transactions on Vehicular Technology, Volume 71, Number 6, June 2022

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In This Issue
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From the IEEE Open Journal of Vehicular Technology
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From the IEEE Transactions on Vehicular Technology
Radar Detection in Vehicular Networks
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F. Richard Yu

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