DNN Aided Joint Source-Channel Decoding Scheme for Polar Codes
نویسندگان
چکیده
In this letter, a deep neural network (DNN) aided joint source-channel (JSCC) decoding scheme is proposed for polar codes. the scheme, an integrated factor graph with unfolded structure first designed. Then DNN flooding belief propagation (FBP) algorithm based on factor, in which both source and channel scaling parameters BP are optimized better performance. Experimental results show that, FBP decoder, coded JSCC can have about 2-2.5 dB gain over different statistics p message length NSC = 128 0.2-1 512 system existing decoder.
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ژورنال
عنوان ژورنال: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
سال: 2023
ISSN: ['1745-1337', '0916-8508']
DOI: https://doi.org/10.1587/transfun.2023eal2068