In this paper, we propose a new type of ultimate-Shannon-limit-approaching codes called spatially coupled protograph-based low-density parity-check Hadamard convolutional codes (SC-PLDPCH-CCs), which are constructed by spatially coupling PLDPC-Hadamard block codes. We also develop an efficient decoding algorithm that combines pipeline decoding and layered scheduling for the decoding of SCPLDPCH- CCs. To estimate the decoding thresholds of SC-PLDPCH-CCs, we first propose a layered protograph extrinsic information transfer (PEXIT) algorithm to evaluate the thresholds of spatially coupled PLDPC-Hadamard terminated codes (SC-PLDPCH-TDCs) with a moderate coupling length. With the use of the proposed layered PEXIT method, we develop a genetic algorithm to look for good SC-PLDPCH-TDCs in a systematic way. Subsequently, we extend the coupling length of these SC-PLDPCH-TDCs with good thresholds to form good SC-PLDPCH-CCs. Based on the same set of split protomatrices, we regard the threshold of SC-PLDPCH-TDC as the proxy of SC-PLDPCH-CC when the SC-PLDPCH-TDC with long coupling length has almost the same code rate as the SC-PLDPCH-CC. Results show that our optimized SC-PLDPCH-CCs can achieve comparable thresholds to the block code counterparts. Simulations also illustrate the superiority of the SC-PLDPCH-CCs over the block code counterparts in terms of error performance. Moreover, for the rate-0.00295 SC-PLDPCH-CC, a BER of 1e-7 is achieved at Eb/N0 = -1.45 dB, which is only 0.14 dB from the ultimate Shannon limit.
翻译:在本文中,我们提出了一种新型的最终脱码算法,称为“S-HANN-限值”-分解码码码;为了估计SC-PLDP-CC的分解阈值,我们首先建议采用以空间连接的 Hadamard 变异代码(SC-PLDPCH-CC)构建的以空间连接的PLDPC-Hadamard区块代码(SC-PLDPCH-Hadmard区块代码);我们还开发了一种高效解码算法,结合管道解码和分层排解 SCPLDP-CC CC CC 的解码;为了估计SC-PLDP-CC-CC 的分层分解码阈值,我们首先建议采用以层连接的血压分解码 Ex-TD-DRDFD 数据转换算法(PEX) 以空间连接的PLDPC-HPC-HD 代码(PEX-CH-DD), 将S-D-D-D-C 的精算算算算算出高的S-C-C-C-C-C-C-SLDDDDDLDDD-LD-C 的值, 也将S-C-C-C-C-LD-LD-S-LD-LD-LD-S-LD-LD-LD-LD-S-LD-S-LD-C 代算算算算法 的精算算算算算法,将S-S-S-S-S-S-S-S-S-S-S-C-C 的精算算算算算算算算算出为相同。