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Main Authors: Wang, Jingyi, Wang, Fanggang
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2601.05292
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author Wang, Jingyi
Wang, Fanggang
author_facet Wang, Jingyi
Wang, Fanggang
contents With the increasing threat posed by modulation classification to wireless security, this paper proposes a secure communication framework based on modulation order confusion (MOC), which intentionally disguises the original modulation as a higher- or lower-order one to mislead eavesdroppers. For single-antenna systems, two schemes are developed: symbol random mapping and symbol time diversity, enabling modulation order confusion with customized receivers. For multi-antenna systems, receiver-transparent MOC schemes are proposed, including series-expansion-based and constellation-path-based signal designs, and are further extended to RIS-assisted systems with joint beamformer and RIS reflection design. Numerical results show that the proposed schemes effectively defeat both deep-learning-based and expert-knowledge-based modulation classifiers without degrading communication performance.
format Preprint
id arxiv_https___arxiv_org_abs_2601_05292
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Secure Communication via Modulation Order Confusion
Wang, Jingyi
Wang, Fanggang
Information Theory
With the increasing threat posed by modulation classification to wireless security, this paper proposes a secure communication framework based on modulation order confusion (MOC), which intentionally disguises the original modulation as a higher- or lower-order one to mislead eavesdroppers. For single-antenna systems, two schemes are developed: symbol random mapping and symbol time diversity, enabling modulation order confusion with customized receivers. For multi-antenna systems, receiver-transparent MOC schemes are proposed, including series-expansion-based and constellation-path-based signal designs, and are further extended to RIS-assisted systems with joint beamformer and RIS reflection design. Numerical results show that the proposed schemes effectively defeat both deep-learning-based and expert-knowledge-based modulation classifiers without degrading communication performance.
title Secure Communication via Modulation Order Confusion
topic Information Theory
url https://arxiv.org/abs/2601.05292