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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.21593 |
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| _version_ | 1866918107046477824 |
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| author | Zhang, Erdeng Zheng, Shuntian Wu, Sheng Jia, Haoge Ji, Zhe Xiao, Ailing |
| author_facet | Zhang, Erdeng Zheng, Shuntian Wu, Sheng Jia, Haoge Ji, Zhe Xiao, Ailing |
| contents | Massive multiple input and multiple output (MIMO) systems with orthogonal frequency division multiplexing (OFDM) are foundational for downlink multi-user (MU) communication in future wireless networks, for their ability to enhance spectral efficiency and support a large number of users simultaneously. However, high user density intensifies severe inter-user interference (IUI) and pilot overhead. Consequently, existing blind and semi-blind channel estimation (CE) and signal detection (SD) algorithms suffer performance degradation and increased complexity, especially when further challenged by frequency-selective channels and high-order modulation demands. To this end, this paper proposes a novel semi-blind joint channel estimation and signal detection (JCESD) method. Specifically, the proposed approach employs a hybrid precoding architecture to suppress IUI. Furthermore we formulate JCESD as a non-convex constellation fitting optimization exploiting constellation affine invariance. Few pilots are used to achieve coarse estimation for initialization and ambiguity resolution. For high-order modulations, a data augmentation mechanism utilizes the symmetry of quadrature amplitude modulation (QAM) constellations to increase the effective number of samples. To address frequency-selective channels, CE accuracy is then enhanced via an iterative refinement strategy that leverages improved SD results. Simulation results demonstrate an average throughput gain of 11\% over widely used pilot-based methods in MU scenarios, highlighting the proposed method's potential to improve spectral efficiency. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_21593 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Affine Invariant Semi-Blind Receiver: Joint Channel Estimation and High-Order Signal Detection for Multiuser Massive MIMO-OFDM Systems Zhang, Erdeng Zheng, Shuntian Wu, Sheng Jia, Haoge Ji, Zhe Xiao, Ailing Signal Processing Massive multiple input and multiple output (MIMO) systems with orthogonal frequency division multiplexing (OFDM) are foundational for downlink multi-user (MU) communication in future wireless networks, for their ability to enhance spectral efficiency and support a large number of users simultaneously. However, high user density intensifies severe inter-user interference (IUI) and pilot overhead. Consequently, existing blind and semi-blind channel estimation (CE) and signal detection (SD) algorithms suffer performance degradation and increased complexity, especially when further challenged by frequency-selective channels and high-order modulation demands. To this end, this paper proposes a novel semi-blind joint channel estimation and signal detection (JCESD) method. Specifically, the proposed approach employs a hybrid precoding architecture to suppress IUI. Furthermore we formulate JCESD as a non-convex constellation fitting optimization exploiting constellation affine invariance. Few pilots are used to achieve coarse estimation for initialization and ambiguity resolution. For high-order modulations, a data augmentation mechanism utilizes the symmetry of quadrature amplitude modulation (QAM) constellations to increase the effective number of samples. To address frequency-selective channels, CE accuracy is then enhanced via an iterative refinement strategy that leverages improved SD results. Simulation results demonstrate an average throughput gain of 11\% over widely used pilot-based methods in MU scenarios, highlighting the proposed method's potential to improve spectral efficiency. |
| title | Affine Invariant Semi-Blind Receiver: Joint Channel Estimation and High-Order Signal Detection for Multiuser Massive MIMO-OFDM Systems |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2507.21593 |