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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/2509.17735 |
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| _version_ | 1866915506653495296 |
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| author | Clausius, Jannis Schmid, Luca Schmalen, Laurent Brink, Stephan ten |
| author_facet | Clausius, Jannis Schmid, Luca Schmalen, Laurent Brink, Stephan ten |
| contents | Iterative message passing detection based on expectation propagation(EP) has demonstrated near-optimum performance in many signal processing and communication scenarios. The method remains feasible even for channel impulse responses (CIRs), where the optimal Bahl-Cocke-Jelinek-Raviv (BCJR) detector is infeasible. However, significant performance degradation occurs for channels with strong inter-symbol interference (ISI), where the initial linear minimum mean square error (LMMSE) estimate is inaccurate. We propose an EP-based detector that operates in a transformed signal space obtained by channel shortening. Specifically, instead of the conventional approach that iterates between an LMMSE estimator and a non-linear symbol-wise demapper, the proposed method iterates between a linear channel shortening filter-based estimator and a nonlinear BCJR detector with reduced memory compared to the actual channel. Additionally, we propose a deliberate mismatch between the initialized messages and the initialized covariance used in the linear estimator in the first iteration for faster convergence. The proposed approach is evaluated for the well-known Proakis-C ISI channel and for CIRs from a wireless measurement campaign. We demonstrate improvements of up to 6dB at 2 bits per channel use and an improved performance-complexity trade-off over conventional EP-based detection. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_17735 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Symbol Detection in Inter-Symbol Interference Channels using Expectation Propagation with Channel Shortening Clausius, Jannis Schmid, Luca Schmalen, Laurent Brink, Stephan ten Information Theory Iterative message passing detection based on expectation propagation(EP) has demonstrated near-optimum performance in many signal processing and communication scenarios. The method remains feasible even for channel impulse responses (CIRs), where the optimal Bahl-Cocke-Jelinek-Raviv (BCJR) detector is infeasible. However, significant performance degradation occurs for channels with strong inter-symbol interference (ISI), where the initial linear minimum mean square error (LMMSE) estimate is inaccurate. We propose an EP-based detector that operates in a transformed signal space obtained by channel shortening. Specifically, instead of the conventional approach that iterates between an LMMSE estimator and a non-linear symbol-wise demapper, the proposed method iterates between a linear channel shortening filter-based estimator and a nonlinear BCJR detector with reduced memory compared to the actual channel. Additionally, we propose a deliberate mismatch between the initialized messages and the initialized covariance used in the linear estimator in the first iteration for faster convergence. The proposed approach is evaluated for the well-known Proakis-C ISI channel and for CIRs from a wireless measurement campaign. We demonstrate improvements of up to 6dB at 2 bits per channel use and an improved performance-complexity trade-off over conventional EP-based detection. |
| title | Symbol Detection in Inter-Symbol Interference Channels using Expectation Propagation with Channel Shortening |
| topic | Information Theory |
| url | https://arxiv.org/abs/2509.17735 |