arXiv:2608. 10517v1 Announce Type: cross Abstract: Accurate physical-layer modeling is increasingly essential for reliable ultra-wideband operation and capacity optimization, especially under the intensified inter-channel stimulated Raman scattering (ISRS) effect.
arXiv:2507. 06849v3 Announce Type: replace-cross Abstract: Neural network (NN)-based Digital Predistortion (DPD) improves linearization for wideband radio frequency (RF) power amplifiers (PAs) but often increases the complexity of the digital back-end.
arXiv:2609.14735v1 Announce Type: cross Abstract: Deep Learning (DL)-based channel estimation has shown high accuracy and low latency in terrestrial 5G NR, but Low Earth Orbit (LEO) Non-Terrestrial N...
arXiv:2607. 08717v1 Announce Type: new Abstract: Narrowband interference (NBI) severely degrades orthogonal frequency-division multiplexing (OFDM) systems by corrupting subcarriers and rendering classical soft demodulation ineffective.
arXiv:2608. 08554v1 Announce Type: cross Abstract: Power amplifier (PA) nonlinearity and memory effects significantly limit the spectral compliance, reliability, and energy efficiency of communication systems.
The paper proposes a measurement-driven multi-layer digital twin framework for terahertz (THz) wireless data centers. It begins with extensive tri-band channel measurements at 140, 220, and 300 GHz to calibrate a physical twin that optimizes geometry, material, antenna, and propagation models. An AI channel twin, built on a line-of-sight aware implicit neural field, learns location-dependent channel statistics to enable real‑time prediction of received power and LoS probability, which feeds into a system‑level evaluation layer that analyzes coverage and interference for AP‑to‑rack and rack‑to‑rack links. Experimental results show the AI twin achieves lower power reconstruction error than existing neural‑field baselines while maintaining real‑time inference, and ceiling‑mounted AP deployment yields over 90% coverage at a 10 dB SINR threshold.
arXiv:2607. 00860v1 Announce Type: cross Abstract: Millimeter-wave (mmWave) beam alignment plays a critical role in next-generation wireless systems, yet its efficient implementation remains challenging.
arXiv:2606. 05754v1 Announce Type: cross Abstract: Phase-sensitive optical time-domain reflectometry ($\phi$-OTDR) is widely used in large-scale distributed acoustic sensing (DAS) because it provides distributed spatiotemporal monitoring over long sensing distances.
arXiv:2506. 18295v2 Announce Type: replace-cross Abstract: Neural ray tracing (RT) has emerged as a promising paradigm for channel modeling by integrating physical propagation principles with neural networks.
arXiv:2609.22294v1 Announce Type: cross Abstract: Underwater Optical Wireless Communication (UOWC) has emerged as a promising technology for high-speed underwater data transmission, offering signific...
Low-light image enhancement (LLIE) methods involve tunable parameters that are typically fixed, often leading to performance degradation when applied across scenes. Manually selecting the best configuration, however, can be time-consuming and not always practical.
We present GB-LSR (Global-Bandwidth Local Spectral Representation), a fixed-grid local spectral representation for continuous image reconstruction. The image domain is partitioned into non-overlapping square patches, each carrying coefficients for a truncated Fourier basis predicted from shared convolutional-encoder features.
arXiv:2607. 20666v1 Announce Type: cross Abstract: The robustness of machine learning techniques across heterogeneous network domains remains an open challenge in optical networks.