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...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Ang, Rosamund Pei Yin
مؤلفون آخرون: Frederique Elise Oggier
التنسيق: Final Year Project
اللغة:English
منشور في: Nanyang Technological University 2022
الموضوعات:
الوصول للمادة أونلاين:https://hdl.handle.net/10356/156951
الوسوم: إضافة وسم
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المؤسسة: Nanyang Technological University
اللغة: English
الوصف
الملخص: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).