solidot新版网站常见问题,请点击这里查看。
消息
本文已被查看131次
A Neural Network Lattice Decoding Algorithm. (arXiv:1807.02913v1 [cs.IT])
来源于:arXiv
Neural network decoding algorithms are recently introduced by Nachmani et al.
to decode high-density parity-check (HDPC) codes. In contrast with iterative
decoding algorithms such as sum-product or min-sum algorithms in which the
weight of each edge is set to $1$, in the neural network decoding algorithms,
the weight of every edge depends on its impact in the transmitted codeword. In
this paper, we provide a novel \emph{feed-forward neural network lattice
decoding algorithm} suitable to decode lattices constructed based on
Construction A, whose underlying codes have HDPC matrices. We first establish
the concept of feed-forward neural network for HDPC codes and improve their
decoding algorithms compared to Nachmani et al. We then apply our proposed
decoder for a Construction A lattice with HDPC underlying code, for which the
well-known iterative decoding algorithms show poor performances. The main
advantage of our proposed algorithm is that instead of assigning and training
weights for 查看全文>>