Memory Approximate Message Passing
| Autor: | Brian M. Kurkoski, Shunqi Huang, Lei Liu |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Signal Processing (eess.SP)
FOS: Computer and information sciences Minimum mean square error Computer Science - Artificial Intelligence Information Theory (cs.IT) Computer Science - Information Theory Matched filter Linear system Orthogonality principle Relaxation (iterative method) Estimator Mathematics - Statistics Theory Statistics Theory (math.ST) Fixed point Matrix (mathematics) Artificial Intelligence (cs.AI) FOS: Electrical engineering electronic engineering information engineering FOS: Mathematics Electrical Engineering and Systems Science - Signal Processing Algorithm Mathematics |
| Zdroj: | ISIT |
| DOI: | 10.1109/isit45174.2021.9518123 |
| Popis: | Approximate message passing (AMP) is a low-cost iterative parameter-estimation technique for certain high-dimensional linear systems with non-Gaussian distributions. However, AMP only applies to independent identically distributed (IID) transform matrices, but may become unreliable for other matrix ensembles, especially for ill-conditioned ones. To handle this difficulty, orthogonal/vector AMP (OAMP/VAMP) was proposed for general right-unitarily-invariant matrices. However, the Bayes-optimal OAMP/VAMP requires high-complexity linear minimum mean square error estimator. To solve the disadvantages of AMP and OAMP/VAMP, this paper proposes a memory AMP (MAMP), in which a long-memory matched filter is proposed for interference suppression. The complexity of MAMP is comparable to AMP. The asymptotic Gaussianity of estimation errors in MAMP is guaranteed by the orthogonality principle. A state evolution is derived to asymptotically characterize the performance of MAMP. Based on the state evolution, the relaxation parameters and damping vector in MAMP are optimized. For all right-unitarily-invariant matrices, the optimized MAMP converges to OAMP/VAMP, and thus is Bayes-optimal if it has a unique fixed point. Finally, simulations are provided to verify the validity and accuracy of the theoretical results. 6 pages, 5 figures, accepted by IEEE ISIT 2021. arXiv admin note: substantial text overlap with arXiv:2012.10861 |
| Databáze: | OpenAIRE |
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