@article{Zhang2026, 
author = {Yu Zhang and Jiarui Yan and Yue Liu and Chunxiao Jiang and Zhijin Qin},
title = {MIMO-OTFS based semantic-aware image transmission under high-mobility scenarios},
year = {2026},
journal = {C2 Science and Technology},
volume = {1},
number = {1},
pages = {63-72},
keywords = {high-mobility, semantic communication, MIMO-OTFS, semantic importance, channel allocation},
url = {https://www.sciopen.com/article/10.26599/C2ST.2026.9700007},
doi = {10.26599/C2ST.2026.9700007},
abstract = {To address performance degradation in semantic communication (SC) systems operating over time-frequency doubly-selective channels in high-mobility environments, this paper introduces a novel framework that integrates multiple-input multiple-output orthogonal time frequency space (MIMO-OTFS) modulation with semantic-aware resource allocation. The proposed approach intelligently maps semantic features to sub-channels based on both their relative importance and the instantaneous quality of each sub-channel. In this scheme, an entropy-based model quantifies the significance of individual semantic components, while the Kendall correlation coefficient is used to measure the consistency between feature importance and sub-channel conditions. The encoder and decoder are jointly trained using a composite loss function that jointly optimizes image classification accuracy, reconstruction fidelity, and sub-channel matching effectiveness. Simulation results show that, under high-mobility channels, the proposed MIMO-OTFS-SC scheme with semantic-aware sub-channel allocation reconstructs images more accurately than the orthogonal frequency division multiplexing-based semantic communication baseline.}
}