Enhancing Sensing-Assisted Communications in Cluttered Indoor Environments through Background Subtraction
Andrea Ramos, Musa Furkan Keskin, Henk Wymeersch, Saul Inca, Jose F., Monserrat

TL;DR
This paper introduces a background subtraction method for sensing-assisted communications in cluttered indoor environments, significantly improving data rates by enabling accurate user detection and tracking in industrial scenarios.
Contribution
It proposes a novel background subtraction technique for clutter removal in indoor SAC, validated with realistic ray tracing simulations based on 3GPP factory models.
Findings
Enhanced data rate performance close to ideal scenarios
Effective clutter removal enables precise user tracking
Significant improvement over existing SAC benchmarks
Abstract
Integrated sensing and communications (ISAC) is poised to be a native technology for the forthcoming Sixth Generation (6G) era, with an emphasis on its potential to enhance communications performance through the integration of sensing information, i.e., sensing-assisted communications (SAC). Nevertheless, existing research on SAC has predominantly confined its focus to scenarios characterized by minimal clutter and obstructions, largely neglecting indoor environments, particularly those in industrial settings, where propagation channels involve high clutter density. To address this research gap, background subtraction is proposed on the monostatic sensing echoes, which effectively addresses clutter removal and facilitates detection and tracking of user equipments (UEs) in cluttered indoor environments with SAC. A realistic evaluation of the introduced SAC strategy is provided, using ray…
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Taxonomy
TopicsIndoor and Outdoor Localization Technologies · Millimeter-Wave Propagation and Modeling · Precipitation Measurement and Analysis
Methods1x1 Convolution · Dilated Convolution · Average Pooling · Convolution · Global Average Pooling · Switchable Atrous Convolution · Focus
