Complete awareness of the wireless environment, crucial for future intelligent networks, requires sensing all transmitted signals, not just the strongest. A fundamental barrier is estimating the target signal when it is buried under strong co-channel interference from other transmitters, a failure of which renders the signal unusable. This work proposes a maximum likelihood (ML)-based cross-preamble estimation framework that exploits carrier frequency offset (CFO) constancy across beam-swept synchronization signals (SS), coherently aggregating information across multiple observations to reinforce the desired signal against overwhelming interference. Cramer-Rao lower bound (CRLB) analysis and simulation demonstrate reliable estimation even when the signal is over a thousand times weaker than the interference. A low-altitude radio-map case study further verifies the framework's practical effectiveness.
@article{arxiv.2510.14806,
title = {Joint Channel and CFO Estimation From Beam-Swept Synchronization Signal Under Strong Inter-Cell Interference},
author = {Bowen Li and Junting Chen and Nikolaos Pappas},
journal= {arXiv preprint arXiv:2510.14806},
year = {2026}
}