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A New Distance-Based Algorithm for Block Turbo Codes: from Concept to Implementation

机译:块涡轮码代码的新距离算法:从概念到实现

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List-based algorithms for decoding Block Turbo Codes (BTC) have gained popularity due to their low computational complexity. The normal way to calculate the soft outputs involves searching for a decision code word D and a competing codeword B. In addition, a scaling factor α and an estimated reliability value β are used. In this paper, we present a new approach that does not require α and β. Soft outputs are generated based on the Euclidean distance property of decision codewords. More importantly, such algorithm has very low computational complexity and is very attractive for practical applications. Based on the synthesis result of FPGA (Field Programmable Gate Array) implementations of the new algorithm, significant complexity saving (up to 79%) is achieved compared to commercially available products. In terms of error performance, we observe certain improvement (0.3 dB coding gain) for BTCs of large Hamming distance and negligible performance degradation for BTCs of short Hamming distance.
机译:用于解码块Turbo代码的列出的基于列出的算法(BTC)由于其低计算复杂性而获得了普及。计算软输出的正常方法涉及搜索决策码D和竞争码字B.此外,使用缩放因子α和估计的可靠性值β。在本文中,我们提出了一种不需要α和β的新方法。基于判决码字的欧几里德距离属性生成软输出。更重要的是,这种算法的计算复杂度非常低,对实际应用非常有吸引力。基于新算法的FPGA(现场可编程门阵列)实现的合成结果,与商业上可获得的产品相比,实现了显着的复杂性节省(高达79%)。在误差性能方面,我们遵守大汉明距离的BTC的某些改进(0.3 dB编码增益)以及短汉明距离的BTC的可忽略的性能下降。

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