{"title":"上行电缆OFDMA信号的定时同步","authors":"Yayi Xiao, B. Berscheid, Ha H. Nguyen, J. Salt","doi":"10.1109/PACRIM47961.2019.8985094","DOIUrl":null,"url":null,"abstract":"The most recent broadband data-over-cable standard, known as DOCSIS 3.1, introduced orthogonal frequency-division multiplexing (OFDM) as a major upgrade to improve transmission efficiency. Because OFDM signals are sensitive to synchronization errors, accurate timing recovery is an integral part of a DOCSIS 3.1 system. Many conventional OFDM/OFDMA timing synchronization methods cannot be directly applied, as they require the use of specific training signals which are incompatible with DOCSIS 3.1. In this paper, the performance of a modified Schmidl and Cox (S&C) timing algorithm is first investigated for DOCSIS 3.1 systems and shown to be unsatisfactory under severe channel conditions. Two novel timing algorithms are proposed which take advantage of the mirrored symmetry of the training signal defined in DOCSIS 3.1. It is demonstrated that both algorithms provide accurate timing estimates even under severe channel conditions and heavy traffic flow. The second algorithm is introduced to eliminate the use of multipliers in the first algorithm, hence reducing the hardware complexity. Data skipping and data truncation are also presented as methods of further reducing the hardware complexity and the corresponding cost-performance tradeoff is investigated.","PeriodicalId":152556,"journal":{"name":"2019 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Timing Synchronization for Upstream Cable OFDMA Signals\",\"authors\":\"Yayi Xiao, B. Berscheid, Ha H. Nguyen, J. Salt\",\"doi\":\"10.1109/PACRIM47961.2019.8985094\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The most recent broadband data-over-cable standard, known as DOCSIS 3.1, introduced orthogonal frequency-division multiplexing (OFDM) as a major upgrade to improve transmission efficiency. Because OFDM signals are sensitive to synchronization errors, accurate timing recovery is an integral part of a DOCSIS 3.1 system. Many conventional OFDM/OFDMA timing synchronization methods cannot be directly applied, as they require the use of specific training signals which are incompatible with DOCSIS 3.1. In this paper, the performance of a modified Schmidl and Cox (S&C) timing algorithm is first investigated for DOCSIS 3.1 systems and shown to be unsatisfactory under severe channel conditions. Two novel timing algorithms are proposed which take advantage of the mirrored symmetry of the training signal defined in DOCSIS 3.1. It is demonstrated that both algorithms provide accurate timing estimates even under severe channel conditions and heavy traffic flow. The second algorithm is introduced to eliminate the use of multipliers in the first algorithm, hence reducing the hardware complexity. Data skipping and data truncation are also presented as methods of further reducing the hardware complexity and the corresponding cost-performance tradeoff is investigated.\",\"PeriodicalId\":152556,\"journal\":{\"name\":\"2019 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PACRIM47961.2019.8985094\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PACRIM47961.2019.8985094","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
最新的宽带电缆数据标准DOCSIS 3.1引入了正交频分复用(OFDM)作为主要升级,以提高传输效率。由于OFDM信号对同步误差很敏感,所以准确的定时恢复是DOCSIS 3.1系统不可缺少的一部分。许多传统的OFDM/OFDMA定时同步方法不能直接应用,因为它们需要使用与DOCSIS 3.1不兼容的特定训练信号。本文首先研究了一种改进的Schmidl and Cox (S&C)定时算法在DOCSIS 3.1系统中的性能,结果表明该算法在恶劣信道条件下的性能并不令人满意。利用DOCSIS 3.1中定义的训练信号的镜像对称性,提出了两种新的定时算法。结果表明,即使在恶劣的信道条件和交通流量较大的情况下,两种算法也能提供准确的时序估计。引入第二种算法是为了消除第一种算法中乘法器的使用,从而降低硬件复杂性。数据跳过和数据截断作为进一步降低硬件复杂度的方法也被提出,并研究了相应的成本性能权衡。
Timing Synchronization for Upstream Cable OFDMA Signals
The most recent broadband data-over-cable standard, known as DOCSIS 3.1, introduced orthogonal frequency-division multiplexing (OFDM) as a major upgrade to improve transmission efficiency. Because OFDM signals are sensitive to synchronization errors, accurate timing recovery is an integral part of a DOCSIS 3.1 system. Many conventional OFDM/OFDMA timing synchronization methods cannot be directly applied, as they require the use of specific training signals which are incompatible with DOCSIS 3.1. In this paper, the performance of a modified Schmidl and Cox (S&C) timing algorithm is first investigated for DOCSIS 3.1 systems and shown to be unsatisfactory under severe channel conditions. Two novel timing algorithms are proposed which take advantage of the mirrored symmetry of the training signal defined in DOCSIS 3.1. It is demonstrated that both algorithms provide accurate timing estimates even under severe channel conditions and heavy traffic flow. The second algorithm is introduced to eliminate the use of multipliers in the first algorithm, hence reducing the hardware complexity. Data skipping and data truncation are also presented as methods of further reducing the hardware complexity and the corresponding cost-performance tradeoff is investigated.