发帖
雷达卡
摘要翻译：
极性码被广泛认为是最近信道编码中最令人兴奋的发现之一。对于短到中等的块长度，它们在列表译码下的纠错性能优于其他现代纠错码。然而，具有中等复杂度的高速基于列表的解码器的实现具有挑战性。串行对消(SC)翻转译码在复杂度很小的情况下，与列表译码相比，具有竞争性的纠错性能，但存在执行时间可变和最坏情况下延迟较大的问题。在这项工作中，我们展示了如何改进目前最先进的高速SC译码算法，以纳入SC-flip的思想。给出了算法的改进以及针对硬件实现的平均执行时间结果。结果表明，本文提出的fast-SSC-flip算法在保持相当纠错性能的前提下，译码速度比前人的工作提高了近一个数量级。
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英文标题：
《Fast-SSC-Flip Decoding of Polar Codes》
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作者：
Pascal Giard and Andreas Burg
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最新提交年份：
2018
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分类信息：
一级分类：Electrical Engineering and Systems Science 电气工程与系统科学
二级分类：Signal Processing 信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
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一级分类：Computer Science 计算机科学
二级分类：Information Theory 信息论
分类描述：Covers theoretical and experimental aspects of information theory and coding. Includes material in ACM Subject Class E.4 and intersects with H.1.1.
涵盖信息论和编码的理论和实验方面。包括ACM学科类E.4中的材料，并与H.1.1有交集。
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一级分类：Mathematics 数学
二级分类：Information Theory 信息论
分类描述：math.IT is an alias for cs.IT. Covers theoretical and experimental aspects of information theory and coding.
它是cs.it的别名。涵盖信息论和编码的理论和实验方面。
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英文摘要：
Polar codes are widely considered as one of the most exciting recent discoveries in channel coding. For short to moderate block lengths, their error-correction performance under list decoding can outperform that of other modern error-correcting codes. However, high-speed list-based decoders with moderate complexity are challenging to implement. Successive-cancellation (SC)-flip decoding was shown to be capable of a competitive error-correction performance compared to that of list decoding with a small list size, at a fraction of the complexity, but suffers from a variable execution time and a higher worst-case latency. In this work, we show how to modify the state-of-the-art high-speed SC decoding algorithm to incorporate the SC-flip ideas. The algorithmic improvements are presented as well as average execution-time results tailored to a hardware implementation. The results show that the proposed fast-SSC-flip algorithm has a decoding speed close to an order of magnitude better than the previous works while retaining a comparable error-correction performance.
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PDF链接：
https://arxiv.org/pdf/1712.00256
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