Literature Database Entry

rezaei2026mobility-aware

Atefeh Rezaei, Mathis Carl and Falko Dressler, "Mobility-Aware Interference-Coupled ISAC for Energy-Efficient Multi-Vehicle Tracking," Proceedings of 28th IEEE International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM 2026), Paris, France, October 2026. (to appear)

Abstract

Integrated sensing and communications (ISAC) has emerged as a promising technology for future vehicular networks by enabling simultaneous wireless communication and environmental sensing using shared spectrum and hardware resources. However, realizing energy-efficient multi-vehicle operation in millimeter wave (mmWave) environments remains challenging due to high mobility, inter-vehicle interference, and the strong coupling between sensing and communication performance. In this paper, we propose a mobility-aware interference-coupled ISAC framework for multi-vehicle tracking in mmWave vehicle-to-infrastructure networks. Accurate sensing and tracking of vehicle states enables efficient predictive beamforming, while the associated transmit power allocation is jointly optimized for energy efficiency under communication quality-of-service and sensing reliability requirements. To accurately capture dense vehicular deployments, inter-vehicle interference is explicitly modeled in both radar sensing and communication links, resulting in a non-convex fractional optimization problem. An efficient alternating optimization framework combining Dinkelbach's method and successive convex approximation is developed to solve the resulting problem with manageable computational complexity. Simulation results demonstrate that the proposed framework substantially improves energy efficiency while maintaining accurate multi-vehicle tracking under realistic interference conditions. Compared with existing predictive beamforming approaches, the proposed scheme achieves higher average energy efficiency and robust tracking performance across varying traffic densities, mobility levels, and noise conditions. Furthermore, the results reveal a fundamental trade-off between sensing reliability and energy efficiency that becomes increasingly pronounced in dense vehicular scenarios, highlighting the importance of interference-aware resource optimization for next-generation ISAC-enabled transportation systems.

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Atefeh Rezaei
Mathis Carl
Falko Dressler

BibTeX reference

@inproceedings{rezaei2026mobility-aware,
    author = {Rezaei, Atefeh and Carl, Mathis and Dressler, Falko},
    note = {to appear},
    title = {{Mobility-Aware Interference-Coupled ISAC for Energy-Efficient Multi-Vehicle Tracking}},
    publisher = {IEEE},
    address = {Paris, France},
    booktitle = {28th IEEE International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM 2026)},
    month = {10},
    year = {2026},
   }
   
   

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Last modified: 2026-08-31