Dynamic Denoising For Amp Applied To Sparse Regression Inner Codes With Outer Codes

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" summary

Concise claim: embedding LDPC structure into the AMP denoiser via belief propagation yields measurable finite-length gains versus separate decoding, with state-evolution approximations (Berthier–Montanari–Nguyen) still describing the effective Gaussian noise. Implementation uses dynamic denoiser integrates LDPC via BP and a Hadamard subsampled sensing matrix for fast transforms. Multiuser operation runs as parallel per-user AMP with additive Onsager terms and supports user-centric cell‑free MRC combining; empirical curves show a consistent leftward SNR shift (red curve) at practical block lengths.

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" chapters (12)

1. 0:00Introduction
2. 0:22Motivation and outline
3. 1:51LDPC code structure
4. 5:59Message passing basics
5. 8:31Denoising with belief propagation
6. 12:45Single-user performance
7. 15:57Extending to multiple users
8. 19:34Joint multi-user decoding
9. 21:45Cell-free architecture
10. 24:59Empirical results
11. 27:29Conclusion and future work
12. 28:57Q&A

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