dorsal/arxiv
View SchemaSecure Communication via Modulation Order Confusion
| Authors | Jingyi Wang, Fanggang Wang |
|---|---|
| Categories | |
| ArXiv ID | 2601.05292vv1 |
| URL | https://arxiv.org/abs/2601.05292 |
| License | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ |
Abstract
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.
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"date_created": "2026-02-17T05:53:04.876000Z",
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"abstract": "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.",
"arxiv_id": "2601.05292",
"authors": [
"Jingyi Wang",
"Fanggang Wang"
],
"categories": [
"cs.IT",
"math.IT"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"title": "Secure Communication via Modulation Order Confusion",
"url": "https://arxiv.org/abs/2601.05292",
"version": "v1"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "fc0ed0c0-729d-48c0-864f-3aa374416469",
"id": "arXiv Dataset",
"type": "Model",
"variant": "snapshot-2026-01-17",
"version": "0.1.0"
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