Delay-Doppler Domain Signal Processing Aided OFDM (DD-a-OFDM) for 6G and Beyond
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| Main Authors: | , , , , , , , , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866918491408302080 |
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| author | Ma, Yiyan Ai, Bo Yuan, Jinhong Li, Shuangyang Cheng, Qingqing Shi, Zhenguo Yuan, Weijie Wei, Zhiqiang Shafie, Akram Ma, Guoyu Lu, Yunlong Yang, Mi Zhong, Zhangdui |
| author_facet | Ma, Yiyan Ai, Bo Yuan, Jinhong Li, Shuangyang Cheng, Qingqing Shi, Zhenguo Yuan, Weijie Wei, Zhiqiang Shafie, Akram Ma, Guoyu Lu, Yunlong Yang, Mi Zhong, Zhangdui |
| contents | High-mobility scenarios will be a critical part of 6G systems. Since the widely deployed orthogonal frequency division multiplexing (OFDM) waveform suffers from subcarrier orthogonality loss under severe Doppler spread, delay-Doppler domain multi-carrier (DDMC) modulation systems, such as orthogonal time frequency space (OTFS), have been extensively studied. While OTFS can exploit time-frequency (TF) domain channel diversity, it faces challenges including high receiver complexity and inflexible TF resource allocation, making OFDM still the most promising waveform for 6G. In this article, we propose a DD domain signal processing-aided OFDM (DD-a-OFDM) scheme to enhance OFDM performance based on DDMC research insights. First, we design a DD-a-OFDM system structure, retaining the classical OFDM transceiver while incorporating DD domain channel estimation and TF domain equalization. Second, we detail DD domain channel estimation using discrete TF pilots and prove that TF domain inter-carrier interference (ICI) could be transformed into DD domain Gaussian interference. Third, we derive closed-form Cramér-Rao lower bounds (CRLBs) for DD domain channel estimation. Fourth, we develop maximum likelihood (ML) and peak detection-based channel estimators, along with a corresponding TF domain equalizer. Numerical results verify the proposed design, showing that DD-a-OFDM reduces the bit-error rate (BER) compared to classical OFDM and outperforms OTFS in channel estimation accuracy with lower pilot overhead. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_04253 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Delay-Doppler Domain Signal Processing Aided OFDM (DD-a-OFDM) for 6G and Beyond Ma, Yiyan Ai, Bo Yuan, Jinhong Li, Shuangyang Cheng, Qingqing Shi, Zhenguo Yuan, Weijie Wei, Zhiqiang Shafie, Akram Ma, Guoyu Lu, Yunlong Yang, Mi Zhong, Zhangdui Signal Processing High-mobility scenarios will be a critical part of 6G systems. Since the widely deployed orthogonal frequency division multiplexing (OFDM) waveform suffers from subcarrier orthogonality loss under severe Doppler spread, delay-Doppler domain multi-carrier (DDMC) modulation systems, such as orthogonal time frequency space (OTFS), have been extensively studied. While OTFS can exploit time-frequency (TF) domain channel diversity, it faces challenges including high receiver complexity and inflexible TF resource allocation, making OFDM still the most promising waveform for 6G. In this article, we propose a DD domain signal processing-aided OFDM (DD-a-OFDM) scheme to enhance OFDM performance based on DDMC research insights. First, we design a DD-a-OFDM system structure, retaining the classical OFDM transceiver while incorporating DD domain channel estimation and TF domain equalization. Second, we detail DD domain channel estimation using discrete TF pilots and prove that TF domain inter-carrier interference (ICI) could be transformed into DD domain Gaussian interference. Third, we derive closed-form Cramér-Rao lower bounds (CRLBs) for DD domain channel estimation. Fourth, we develop maximum likelihood (ML) and peak detection-based channel estimators, along with a corresponding TF domain equalizer. Numerical results verify the proposed design, showing that DD-a-OFDM reduces the bit-error rate (BER) compared to classical OFDM and outperforms OTFS in channel estimation accuracy with lower pilot overhead. |
| title | Delay-Doppler Domain Signal Processing Aided OFDM (DD-a-OFDM) for 6G and Beyond |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2508.04253 |