MARBLE-Net: Learning to Localize in Multipath Environment with Adaptive Rainbow Beams Article Swipe
Yeyue Cai
,
Jianhua Mo
,
Meixia Tao
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2511.06971
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2511.06971
Integrated sensing and communication (ISAC) systems demand precise and efficient target localization, a task challenged by rich multipath propagation in complex wireless environments. This paper introduces MARBLE-Net (Multipath-Aware Rainbow Beam Learning Network), a deep learning framework that jointly optimizes the analog beamforming parameters of a frequency-dependent rainbow beam and a neural localization network for high-accuracy position estimation. By treating the phase-shifter (PS) and true-time-delay (TTD) parameters as learnable weights, the system adaptively refines its sensing beam to exploit environment-specific multipath characteristics. A structured multi-stage training strategy is proposed to ensure stable convergence and effective end-to-end optimization. Simulation results show that MARBLE-Net outperforms both a fixed-beam deep learning baseline (RaiNet) and a traditional k-nearest neighbors (k-NN) method, reducing localization error by more than 50\% in a multipath-rich scene. Moreover, the results reveal a nuanced interaction with multipath propagation: while confined uni-directional multipath degrades accuracy, structured and directional multipath can be effectively exploited to achieve performance surpassing even line-of-sight (LoS) conditions.
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- Type
- preprint
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- http://arxiv.org/abs/2511.06971
- https://arxiv.org/pdf/2511.06971
- OA Status
- green
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Raw OpenAlex JSON
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https://doi.org/10.48550/arxiv.2511.06971Digital Object Identifier
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MARBLE-Net: Learning to Localize in Multipath Environment with Adaptive Rainbow BeamsWork title
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preprintOpenAlex work type
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2025Year of publication
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2025-11-10Full publication date if available
- Authors
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Yeyue Cai, Jianhua Mo, Meixia TaoList of authors in order
- Landing page
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https://arxiv.org/abs/2511.06971Publisher landing page
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https://arxiv.org/pdf/2511.06971Direct link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2511.06971Direct OA link when available
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0Total citation count in OpenAlex
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