Differentiated Embedded Pilot Assisted Automatic Modulation Classification for OTFS System: A Multi-Domain Fusion Approach
Orthogonal time–frequency space (OTFS) modulation has emerged as a promising technology to alleviate the effects of the Doppler shifts in high-mobility environments. As a prerequisite to demodulation and signal processing, automatic modulation classification (AMC) is essential for OTFS systems. Howe...
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| Format: | Article |
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MDPI AG
2025-07-01
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| Online Access: | https://www.mdpi.com/1424-8220/25/14/4393 |
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| author | Zhenkai Liu Bibo Zhang Hao Luo Hao He |
| author_facet | Zhenkai Liu Bibo Zhang Hao Luo Hao He |
| author_sort | Zhenkai Liu |
| collection | DOAJ |
| description | Orthogonal time–frequency space (OTFS) modulation has emerged as a promising technology to alleviate the effects of the Doppler shifts in high-mobility environments. As a prerequisite to demodulation and signal processing, automatic modulation classification (AMC) is essential for OTFS systems. However, a very limited number of works have focused on this issue. In this paper, we propose a novel AMC approach for OTFS systems. We build a dual-stream convolutional neural network (CNN) model to simultaneously capture multi-domain signal features, which substantially enhances recognition accuracy. Moreover, we propose a differentiated embedded pilot structure that incorporates information about distinct modulation schemes to further improve the separability of modulation types. The results of the extensive experiments carried out show that the proposed approach can achieve high classification accuracy even under low signal-to-noise ratio (SNR) conditions and outperform the state-of-the-art baselines. |
| format | Article |
| id | doaj-art-06cc02b247d6414c8b2e5216ce721df1 |
| institution | DOAJ |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-06cc02b247d6414c8b2e5216ce721df12025-08-20T02:47:05ZengMDPI AGSensors1424-82202025-07-012514439310.3390/s25144393Differentiated Embedded Pilot Assisted Automatic Modulation Classification for OTFS System: A Multi-Domain Fusion ApproachZhenkai Liu0Bibo Zhang1Hao Luo2Hao He3Ocean College, Jiangsu University of Science and Technology, Zhenjiang 212100, ChinaOcean College, Jiangsu University of Science and Technology, Zhenjiang 212100, ChinaOcean College, Jiangsu University of Science and Technology, Zhenjiang 212100, ChinaOcean College, Jiangsu University of Science and Technology, Zhenjiang 212100, ChinaOrthogonal time–frequency space (OTFS) modulation has emerged as a promising technology to alleviate the effects of the Doppler shifts in high-mobility environments. As a prerequisite to demodulation and signal processing, automatic modulation classification (AMC) is essential for OTFS systems. However, a very limited number of works have focused on this issue. In this paper, we propose a novel AMC approach for OTFS systems. We build a dual-stream convolutional neural network (CNN) model to simultaneously capture multi-domain signal features, which substantially enhances recognition accuracy. Moreover, we propose a differentiated embedded pilot structure that incorporates information about distinct modulation schemes to further improve the separability of modulation types. The results of the extensive experiments carried out show that the proposed approach can achieve high classification accuracy even under low signal-to-noise ratio (SNR) conditions and outperform the state-of-the-art baselines.https://www.mdpi.com/1424-8220/25/14/4393automatic modulation classificationorthogonal time–frequency spacemulti-domain fusionembedded pilot |
| spellingShingle | Zhenkai Liu Bibo Zhang Hao Luo Hao He Differentiated Embedded Pilot Assisted Automatic Modulation Classification for OTFS System: A Multi-Domain Fusion Approach Sensors automatic modulation classification orthogonal time–frequency space multi-domain fusion embedded pilot |
| title | Differentiated Embedded Pilot Assisted Automatic Modulation Classification for OTFS System: A Multi-Domain Fusion Approach |
| title_full | Differentiated Embedded Pilot Assisted Automatic Modulation Classification for OTFS System: A Multi-Domain Fusion Approach |
| title_fullStr | Differentiated Embedded Pilot Assisted Automatic Modulation Classification for OTFS System: A Multi-Domain Fusion Approach |
| title_full_unstemmed | Differentiated Embedded Pilot Assisted Automatic Modulation Classification for OTFS System: A Multi-Domain Fusion Approach |
| title_short | Differentiated Embedded Pilot Assisted Automatic Modulation Classification for OTFS System: A Multi-Domain Fusion Approach |
| title_sort | differentiated embedded pilot assisted automatic modulation classification for otfs system a multi domain fusion approach |
| topic | automatic modulation classification orthogonal time–frequency space multi-domain fusion embedded pilot |
| url | https://www.mdpi.com/1424-8220/25/14/4393 |
| work_keys_str_mv | AT zhenkailiu differentiatedembeddedpilotassistedautomaticmodulationclassificationforotfssystemamultidomainfusionapproach AT bibozhang differentiatedembeddedpilotassistedautomaticmodulationclassificationforotfssystemamultidomainfusionapproach AT haoluo differentiatedembeddedpilotassistedautomaticmodulationclassificationforotfssystemamultidomainfusionapproach AT haohe differentiatedembeddedpilotassistedautomaticmodulationclassificationforotfssystemamultidomainfusionapproach |