| Summary: | 碩士 === 國立交通大學 === 電子工程系所 === 98 === Low-density parity-check (LDPC) code was introduced by R.G. Gallager in 1962, which has sparse parity check matrix due to its unique code construction. With sparse parity check matrix, the complexity required for decoding is low. LDPC code has the performance which is closer to Shannon limit than other codes. In this thesis, we apply LDPC codes to product code form so that the iterative decoding of LDPC code includes the concept of turbo decoding. However, for single row (column) decoding in turbo decoding, the extrinsic information generated by soft decoding in sufficiently high iteration number may come with distortion after message interleaving, and hence the performance is degraded. For this distortion, we propose the absolute-mean mapping normalization which achieves a considerable performance improvement with only little additional computational complexity. For example, for turbo (63,37,8,8)^2 EG-LDPC code with LDPC iteration number fixed to 2, its performance is improved at most 1.2dB by this normalization. For LDPC iteraion number fixed to 4, its performance improvement even achieve 2dB. With the absolute-mean mapping normalization, the turbo (63,37,8,8)^2 EG-LDPC code has about 3.4dB performance limit improvement from the original (63,37,8,8) EG-LDPC code.
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