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arXiv · 2203.10281

Min-Max Latency Optimization Based on Sensed Position State Information in Internet of Vehicles

Pengzun Gao·Long Zhao·Kan Zheng·Pingzhi Fan
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Abstract

The dual-function radar communication (DFRC) is an essential technology in Internet of Vehicles (IoV). Consider that the road-side unit (RSU) employs the DFRC signals to sense the vehicles' position state information (PSI), and communicates with the vehicles based on PSI. The objective of this paper is to minimize the maximum communication delay among all vehicles by considering the estimation accuracy constraint of the vehicles' PSI and the transmit power constraint of RSU. By leveraging convex optimization theory, two iterative power allocation algorithms are proposed with different complexities and applicable scenarios. Simulation results indicate that the proposed power allocation algorithm converges and can significantly reduce the maximum transmit delay among vehicles compared with other schemes.

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Pengzun Gao, Long Zhao, Kan Zheng, Pingzhi Fan. 2022-03-19. Min-Max Latency Optimization Based on Sensed Position State Information in Internet of Vehicles. https://arxiv.org/abs/2203.10281

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