|| Proximal Decoding for LDPC-coded Massive MIMO Channels
||Tadashi Wadayama, Satoshi Takabe, Nagoya Institute of Technology, Japan|
||D1-S4-T2: LDPC Codes II
||Monday, 12 July, 23:00 - 23:20
||Monday, 12 July, 23:20 - 23:40
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.