Abstract
Combined with the path splitting selecting (PSS) strategy, the successive cancellation list (SCL) decoder achieves a lower decoding complexity without any performance loss. The main purpose of the PSS strategy is to select fewer non-frozen bits to perform the path splitting and pruning operations. To make the selection more efficient, a neural network aided path splitting selecting strategy is proposed in this paper. In the proposed method, the path splitting is seen as a classification problem. With the help of the neural network, the proposed method can precisely locate the non-frozen bits which are needed to be split. Simulation results verify that the proposed method can reduce the sorting complexity (which is equal to the number of path splitting) without any performance loss.
Original language | English |
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Article number | 10049489 |
Pages (from-to) | 1-5 |
Number of pages | 5 |
Journal | IEEE Transactions on Vehicular Technology |
DOIs | |
Publication status | Published - Feb 2023 |
Keywords
- Artificial neural networks
- Complexity theory
- Maximum likelihood decoding
- neural network
- Neurons
- path splitting
- Polar codes
- Reliability
- Sorting
- successive cancellation list (SCL) decoding
ASJC Scopus subject areas
- Automotive Engineering
- Aerospace Engineering
- Electrical and Electronic Engineering
- Applied Mathematics