The fully-decoupled radio access network (FD-RAN) with multiple base stations (BS) networked cooperation is expected to provide high-quality communication coverage for aerial vehicles while sensing their locations accurately and efficiently. In this paper, we propose a novel multiple BSs cooperative passive integrated sensing and communication (ISAC) framework in FD-RAN for low-altitude aerial vehicles. It utilizes the Doppler shift information from uplink orthogonal frequency division multiplexing (OFDM) signals to achieve efficient localization without incurring additional sensing overhead. Specifically, the carrier frequency offset (CFO) compensation process at each BS captures Doppler shift resulting from the relative motion between the aerial vehicle and the BS. Considering the position and velocity of the aerial vehicle as unknown variables, the localization is achieved by formulating and solving a system of equations describing these Doppler shifts. Furthermore, to enable accurate trajectory tracking, we design a learning-based adaptive double-filter (LADF) algorithm, which leverages temporal correlations in both Doppler shift measurements and vehicle trajectories to improve the time-continuous localization. Extensive simulation results demonstrate the effectiveness of our proposed ISAC framework in low-altitude FD-RAN, which can enhance the coverage performance and efficiently provide accurate localization for aerial vehicles.
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Xue et al. (2026) studied this question.
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