基于递归神经网络的卷积码解码器的研究

Research of Convolutional Decoder Based on Recurrent Neural Network(RNN)

详细介绍了一种基于递归神经网络(RNN)的1/n卷积码解码器的原理与实现。仿真结果表明RNN解码器与Vterbi解码器效果很接近,对一些特殊的卷积码,性能非常好。并通过模拟退火技术对此解码器的性能进行了改善。

In this paper a detailed principle and application of a 1/n rate convolution decoder based on Recurrent Neural Network（RNN） are introduced. Simulation results have confirmed that the RNN decoder is capable of performing very close to the Viterbi decoder and works very well for some specially structured convolution codes. In particular,decoding capabilities of RNN decoders are improved when Simulated Annealing（SA） technique has been used.