Proximal Decoding for LDPC-coded Massive MIMO Channels
| Autor: | Satoshi Takabe, Tadashi Wadayama |
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| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Computer science Computer Science - Information Theory Information Theory (cs.IT) MIMO Code word Recursion (computer science) Data_CODINGANDINFORMATIONTHEORY Maximum a posteriori estimation Proximal Gradient Methods Low-density parity-check code Gradient descent Algorithm Decoding methods Computer Science::Information Theory |
| Zdroj: | ISIT |
| DOI: | 10.1109/isit45174.2021.9517988 |
| Popis: | We propose a novel optimization-based decoding algorithm for LDPC-coded massive MIMO channels. The proposed decoding algorithm is based on a proximal gradient method for solving an approximate maximum a posteriori (MAP) decoding problem. The key idea is the use of a code-constraint polynomial penalizing a vector far from a codeword as a regularizer in the approximate MAP objective function. The code proximal operator is naturally derived from code-constraint polynomials. The proposed algorithm, called proximal decoding, can be described by a simple recursion consisting of the gradient descent step for a negative log-likelihood function and the code proximal operation. Several numerical experiments show that the proposed algorithm outperforms known massive MIMO detection algorithms, such as an MMSE detector with belief propagation decoding. |
| Databáze: | OpenAIRE |
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