Literature Database Entry

carl2025optimized

Mathis Carl, "Optimized V2I Framework for Mobile Target Tracking via Integrated Sensing and Communication," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), November 2025. (Advisor: Atefeh Rezaei; Referees: Falko Dressler and Thomas Sikora)

Abstract

The integration of sensing and communication (ISAC) has emerged as a key enabler for vehicular networks, with the potential to significantly accelerate the realization of autonomous driving. This work investigates an existing radar-assisted predictive beamforming framework designed for vehicle-to-infrastructure (V2I) communication based on dual-functional radar-communication (DFRC) technology. Vehicle states are predicted using a one-step prediction performed by an extended Kalman filter (EKF) tailored to a representative mobility scenario. Beyond noise and line-of-sight (LOS) channel models, interference is explicitly incorporated within the proposed framework. The optimization problem is formulated with the objective of maximizing the overall system energy-efficiency. Since this is a mixed-integer linear fractional programming (MILFP) problem, the Dinkelbach algorithm is combined with successive convex approximation (SCA) to solve the problem efficiently. The Dinkelbach method is particularly suitable as it transforms the fractional objective into a sequence of parameterized linear problems, which can then be efficiently tackled within the SCA approximations. Simulation results demonstrate substantial energy-efficiency gains of the optimized framework compared to a fixed power transmission, while also revealing the decisive impact of vehicle to RSU distance, noise levels, power budgets and the number of tracked vehicles. These findings validate the proposed framework and optimization as well as highlights its relevance for designing future ISAC-based vehicular networks.

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Mathis Carl

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@phdthesis{carl2025optimized,
    author = {Carl, Mathis},
    title = {{Optimized V2I Framework for Mobile Target Tracking via Integrated Sensing and Communication}},
    advisor = {Rezaei, Atefeh},
    institution = {School of Electrical Engineering and Computer Science (EECS)},
    location = {Berlin, Germany},
    month = {11},
    referee = {Dressler, Falko and Sikora, Thomas},
    school = {TU Berlin (TUB)},
    type = {Master's Thesis},
    year = {2025},
   }
   
   

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Last modified: 2026-04-21