...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>IEEE Transactions on Communications >Optimal Training Sequences for Joint Timing Synchronization and Channel Estimation in Distributed Communication Networks
【24h】

Optimal Training Sequences for Joint Timing Synchronization and Channel Estimation in Distributed Communication Networks

机译：分布式通信网络中联合定时同步和信道估计的最优训练序列

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

For distributed multi-user and multi-relay cooperative networks, the received signal may be affected by multiple timing offsets (MTOs) and multiple channels that need to be jointly estimated for successful decoding at the receiver. This paper addresses the design of optimal training sequences for efficient estimation of MTOs and multiple channel parameters. A new hybrid Cramer-Rao lower bound (HCRB) for joint estimation of MTOs and channels is derived. Subsequently, by minimizing the derived HCRB as a function of training sequences, three training sequence design guidelines are derived and according to these guidelines, two training sequences are proposed. In order to show that the proposed design guidelines also improve estimation accuracy, the conditional Cramer-Rao lower bound (ECRB), which is a tighter lower bound on the estimation accuracy compared to the HCRB, is also derived. Numerical results show that the proposed training sequence design guidelines not only lower the HCRB, but they also lower the ECRB and the mean-square error of the proposed maximum a posteriori estimator. Moreover, extensive simulations demonstrate that application of the proposed training sequences significantly lowers the bit-error rate performance of multi-relay cooperative networks when compared to training sequences that violate these design guidelines.
机译：对于分布式多用户和多中继协作网络，接收到的信号可能会受到多个定时偏移（MTO）和多个信道的影响，这些信号需要共同估算才能在接收器处成功解码。本文介绍了用于有效估计MTO和多通道参数的最佳训练序列的设计。推导了一种新的混合式Cramer-Rao下界（HCRB），用于联合估计MTO和通道。随后，通过最小化作为训练序列的函数的导出的HCRB，得出了三个训练序列设计指南，并根据这些指南提出了两个训练序列。为了表明所提出的设计准则还可以提高估计精度，还推导了条件式Cramer-Rao下限（ECRB），与HCRB相比，ECRB是估计精度上更严格的下限。数值结果表明，提出的训练序列设计准则不仅降低了HCRB，而且降低了提出的最大后验估计量的ECRB和均方误差。此外，广泛的仿真表明，与违反这些设计准则的训练序列相比，所提出的训练序列的应用显着降低了多中继协作网络的误码率性能。

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