Novel PDP-Guided Blockage Sensing and Mitigation in Near-Field XL-MIMO Systems

Novel PDP-Guided Blockage Sensing and Mitigation in Near-Field XL-MIMO Systems | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 21 May 2025 V1 Latest version Share on Novel PDP-Guided Blockage Sensing and Mitigation in Near-Field XL-MIMO Systems Authors : Salim M. Yahya 0000-0002-3939-185X [email protected] , Chiza M Christophe , Liza Afeef , and Hüseyin Arslan Authors Info & Affiliations https://doi.org/10.22541/au.174785217.74718460/v1 Published IEEE Transactions on Cognitive Communications and Networking Version of record Peer review timeline 294 views 163 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract This paper presents intelligent blockage detection and mitigation techniques for near-field XL-MIMO systems, where the spatial non-stationarity and spot-like beam behavior exacerbate the impact of environmental blockages. By leveraging the power delay profile (PDP) shaped by spherical wavefronts across the array, we propose two complementary methods for blockage detection: a model-based approach using belief propagation within a Markov Random Field (MRF), and a learningbased approach using a tailored 3D CNN. Both methods operate without external sensing hardware. Based on the estimated blockage map, two self-healing beamforming strategies are explored: (i) a greedy antenna selection method that maximizes postblockage SNR, and (ii) a lightweight codebook-based beam realignment approach. These techniques redistribute transmission energy away from blocked elements, enabling robust communication. Simulation results show that the model-based approach is robust under low-SNR conditions, while the CNN-based model excels at higher SNRs. Importantly, both approaches restore the spectral efficiency to near pre-blockage levels through adaptive beamforming, demonstrating their effectiveness in maintaining high-throughput links under dynamic blockage scenarios. Supplementary Material File (a_novel_rem_for_sensing_assisted_communication_in_xl_mimo__copy_.pdf) Download 9.75 MB Information & Authors Information Version history V1 Version 1 21 May 2025 Peer review timeline Published IEEE Transactions on Cognitive Communications and Networking Version of Record 1 Jan 2026 Published Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords beam healing beamforming blockage detection blockage mitigation convolutional neural networks (cnn) greedy antenna selection intelligent signal processing near-field communication power delay profile (pdp) radio environment map (rem) xl-mimo Authors Affiliations Salim M. Yahya 0000-0002-3939-185X [email protected] View all articles by this author Chiza M Christophe View all articles by this author Liza Afeef View all articles by this author Hüseyin Arslan View all articles by this author Metrics & Citations Metrics Article Usage 294 views 163 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Salim M. Yahya, Chiza M Christophe, Liza Afeef, et al. Novel PDP-Guided Blockage Sensing and Mitigation in Near-Field XL-MIMO Systems. Authorea . 21 May 2025. DOI: https://doi.org/10.22541/au.174785217.74718460/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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