Polar code SSCL algorithm decoder based on deep learning

A polar code and decoder technology, applied in the field of polar code decoder, can solve problems such as high delay, and achieve the effect of reducing decoding delay

Pending Publication Date: 2019-08-16
CHINA JILIANG UNIV
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Problems solved by technology

[0005] In order to solve the problem that SSCL has a higher delay for nodes other than special nodes, the present invention provides a decoder combined with the SSCL decoding algorithm of deep learning neural

Method used

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  • Polar code SSCL algorithm decoder based on deep learning
  • Polar code SSCL algorithm decoder based on deep learning
  • Polar code SSCL algorithm decoder based on deep learning

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Embodiment Construction

[0030] The present invention will be described in further detail below in conjunction with the accompanying drawings. The following examples are helpful to the understanding of the present invention and are better application examples, but should not be regarded as a limitation of the present invention.

[0031] Such as figure 1 As shown, the present invention includes 5 calculation modules, normal SCL calculation module, Rate-0 calculation module, Rep calculation module, Rate-1 calculation module and DNN calculation module of ordinary nodes, and tree decoding is used in the SCL decoding process In this method, the normal SCL calculation is used from the root node to a certain layer in the middle, and then the codewords are classified at this layer. Four calculations are introduced to achieve the purpose of decoding the codewords in advance and stopping the rest of the tree search.

[0032] Such as figure 2 As shown, here, for the convenience of explanation, the code length ...

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Abstract

The invention provides a low-time-delay polar code decoder combined with deep learning, and particularly, compared with a simplified Successive cancellation list (SSCL) decoder, the low-time-delay polar code decoder has the advantage that the number of calculation times is smaller. The decoder comprises five modules, namely a normal SCL calculation module, a Rate-0 calculation module, a Rep calculation module, a Rate-1 calculation module, and a DNN calculation module of a common node. The SSCL decoder combined with the deep neural network retains the original low decoding delay characteristicof Rate-0, Rate-1 and Rep nodes, a deep neural network is used for decoding common nodes to reduce the decoding delay, and finally the purpose of reducing the overall decoding delay is achieved. Experimental calculation shows that when the code length is 64 and the code rate is 1/2, the decoding delay is reduced by about 27% compared with the decoding delay of the SSCL.

Description

technical field [0001] The invention belongs to the technical field of decoding of communication channel coding, and relates to a polar code decoder combined with deep learning, in particular, a decoder with fewer calculation times compared with the traditional SSCL algorithm, reaching A Polar Code Decoder Using Deep Learning to Reduce Decoding Latency Effects. Background technique [0002] Since the establishment of channel coding theory, channel coding technology has experienced decades of development and innovation. As a coding technology proposed in the past ten years, polar codes have a specific codec structure like algebraic codes, and also use channel polarization to establish a theoretical basis for codecs. Polar codes obtain several split channels through two operations of channel combination and channel splitting, and their capacity shows a trend of polarization, that is, as the code length increases, either tends to a completely noisy channel, or tends to a compl...

Claims

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Application Information

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IPC IPC(8): H03M13/13G06N3/04
CPCH03M13/13G06N3/045
Inventor 王秀敏何金隆单良洪波
Owner CHINA JILIANG UNIV
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