Simultaneous Source Separation, Synchronization, Localization and Mapping for 6G Systems
Alexander Venus Erik Leitinger Klaus Witrisal
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Abstract
Multipath-based simultaneous localization and mapping (MP-SLAM) is a promising approach for future 6G networks to jointly estimate the positions of transmitters and receivers together with the propagation environment. In cooperative MP-SLAM, information collected by multiple mobile terminals (MTs) is fused to enhance accuracy and robustness. Existing methods, however, typically assume perfectly synchronized base stations (BSs) and orthogonal transmission sequences, rendering inter-BS interference at the MTs negligible. In this work, we relax these assumptions and address simultaneous source separation, synchronization, and mapping. A relevant example arises in modern 5G systems, where BSs employ muting patterns to mitigate interference, yet localization performance still degrades. We propose a novel BS-dependent data association and synchronization bias model, integrated into a joint Bayesian framework and inferred via the sum-product algorithm on a factor graph. The impact of joint synchronization and source separation is analyzed under various system configurations. Compared with state-of-the-art cooperative MP-SLAM assuming orthogonal and synchronized BSs, our statistical analysis shows no significant performance degradation. The proposed BS-dependent data association model constitutes a principled approach for classifying features by arbitrary properties, such as reflection order or feature type (scatterers versus walls).引用本文复制引用
Alexander Venus,Erik Leitinger,Klaus Witrisal.Simultaneous Source Separation, Synchronization, Localization and Mapping for 6G Systems[EB/OL].(2025-12-30)[2026-01-17].https://arxiv.org/abs/2512.22393.学科分类
通信/无线通信
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