Optimisation of reinforcement learning-based decoding strategies for binary linear codes
Linear codes are a class of error-correcting codes, whereby any linear combination of two codewords always results in another codeword. In general, they are defined over a finite field, and have broad applications in the fields of communications and information systems. The present work surveys the...
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| 格式: | Final Year Project |
| 語言: | English |
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Nanyang Technological University
2022
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| 在線閱讀: | https://hdl.handle.net/10356/156951 |
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| 機構: | Nanyang Technological University |
| 語言: | English |
| 總結: | Linear codes are a class of error-correcting codes, whereby any linear combination of two codewords always results in another codeword. In general, they are defined over a finite field, and have broad applications in the fields of communications and information systems. The present work surveys the construction and decoding methods for binary linear codes, and approaches the decoding of such linear codes as a reinforcement learning (RL) problem. The present work also presents a general theoretical RL-based framework for the decoding of binary linear codes over a binary symmetric channel (BSC). |
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