首页> 外文期刊>Broadcasting, IEEE Transactions on >Signal-to-Noise Ratio Estimation Algorithm for Advanced DVB-RCS Systems
【24h】

Signal-to-Noise Ratio Estimation Algorithm for Advanced DVB-RCS Systems

机译:先进DVB-RCS系统的信噪比估计算法

获取原文
获取原文并翻译 | 示例

摘要

This paper presents a signal-to-noise ratio (SNR) estimation algorithm for advanced Digital Video Broadcasting-Return Channel via Satellite (DVB-RCS) systems using adaptive coding and modulation (ACM) in the reverse link of broadband satellite systems. Due to the absence of a repetitive pilot symbol structure, SNR estimation has to be performed using the fixed symbol preamble data. Moreover, sporadic nature of data traffic on the return link causes variation in interference level from slot to slot and, therefore, the estimation has to be done within one traffic slot duration. Hence, it becomes necessary to use a combination of data-aided (DA) and decision-directed (DD) algorithms so as to make use of traffic data. A non-data-aided (NDA) estimator that was previously proposed by the authors for binary phase shift keying (BPSK) and QPSK schemes is extended to 8-PSK in a decision directed manner. This estimator shows improved performance over existing estimators. The inherent bias of DD approach at low values of SNR is reduced by using a hybrid approach, i.e., using the proposed estimator at moderate/high values of SNR and the moments-based estimator $(M_{2}M_{4})$ at low values of SNR. Overall improved performance of the proposed hybrid estimator, in terms of accuracy and complexity, makes it an attractive choice for implementing ACM in advanced DVB-RCS systems.
机译:本文提出了一种在宽带卫星系统反向链路中使用自适应编码和调制(ACM)的高级数字视频卫星回传信道(DVB-RCS)系统的信噪比(SNR)估计算法。由于不存在重复的导频符号结构,因此必须使用固定符号前导数据来执行SNR估计。此外,返回链路上数据流量的零星性质会导致时隙之间的干扰水平发生变化,因此,必须在一个流量时隙持续时间内进行估算。因此,有必要使用数据辅助(DA)和决策导向(DD)算法的组合,以便利用交通数据。作者先前提出的用于二进制相移键控(BPSK)和QPSK方案的非数据辅助(NDA)估计器以决策导向的方式扩展为8-PSK。该估算器显示出比现有估算器更高的性能。通过使用混合方法,可以降低DD方法在SNR低值时的固有偏差,即使用建议的估算器在SNR中/高值时以及基于矩的估算器$(M_ {2} M_ {4})$在低SNR值时。就准确性和复杂性而言,所提出的混合估计器的整体性能得到了改善,使其成为在高级DVB-RCS系统中实施ACM的有吸引力的选择。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号