Cooperative Mapping, Localization, and Beam Management via Multi-Modal SLAM in ISAC Systems
Journal:
arXiv
Published Date:
Jul 8, 2025
Abstract
Simultaneous localization and mapping (SLAM) plays a critical role in
integrated sensing and communication (ISAC) systems for sixth-generation (6G)
millimeter-wave (mmWave) networks, enabling environmental awareness and precise
user equipment (UE) positioning. While cooperative multi-user SLAM has
demonstrated potential in leveraging distributed sensing, its application
within multi-modal ISAC systems remains limited, particularly in terms of
theoretical modeling and communication-layer integration. This paper proposes a
novel multi-modal SLAM framework that addresses these limitations through three
key contributions. First, a Bayesian estimation framework is developed for
cooperative multi-user SLAM, along with a two-stage algorithm for robust radio
map construction under dynamic and heterogeneous sensing conditions. Second, a
multi-modal localization strategy is introduced, fusing SLAM results with
camera-based multi-object tracking and inertial measurement unit (IMU) data via
an error-aware model, significantly improving UE localization in multi-user
scenarios. Third, a sensing-aided beam management scheme is proposed, utilizing
global radio maps and localization data to generate UE-specific prior
information for beam selection, thereby reducing inter-user interference and
enhancing downlink spectral efficiency. Simulation results demonstrate that the
proposed system improves radio map accuracy by up to 60%, enhances localization
accuracy by 37.5%, and significantly outperforms traditional methods in both
indoor and outdoor environments.
