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Multistatic ISAC with Deep Learning-Based Clutter Suppression for 5G and Beyond

Paper recorded by Signals 4 on 2026-10-29 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-29 on arXiv · recorded by Signals 4 on 2026-10-30

Category: cs.AI · 人工智能 · first seen 2026-10-30

Abstract

Integrated sensing and communications (ISAC) systems using 5G and beyond signals of opportunity enable joint wireless sensing and communication using shared infrastructure and spectrum resources. While multistatic ISAC can increase sensing coverage with spatially distributed receivers, dense and dynamic clutter can significantly degrade bistatic range and Doppler estimation, leading to errors in t

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#70 most recent of 920 cs.AI papers we have recorded · ↑ newer: Pre-Crime for Agents, at the Last Second: Probing When a Recruited Age · ↓ older: VeriCUA: Verification as Agentic Exploration for Computer-Using Agents
Cite this page: Multistatic ISAC with Deep Learning-Based Clutter Suppression for 5G and Beyond: the #70 most recent of 920 cs.AI papers we have recorded (as of 2026-10-29). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/multistatic-isac-with-deep-learning-based-clutter-suppression-for-5g-and-beyond.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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