Optimal Pilot Design for Data Dependent Superimposed Training based Channel Estimation in Single/Multi carrier Block Transmission Systems

Manjeer Majumder, A. Jagannatham
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引用次数: 0

Abstract

This paper develops a novel data dependent superimposed training technique for channel estimation in generic block transmission (BT) systems comprising of single/multi-carrier (SC/MC) and zero-padded (ZP)/ cyclic prefix (CP) systems. The training sequence comprises of the summation of a known training sequence and a data-dependent sequence that is not known to the receiver. A unique aspect of the scheme is that the channel estimation is not affected by the use of a data-dependent sequence. The pilot design framework is conceived in order to minimize the Bayesian Cramér-Rao bound (BCRB) associated with channel estimation error. Simulation results are provided to exhibit the performance of the proposed scheme for single and multi carrier zero-padded and cyclic prefixed systems.
单/多载波块传输系统中基于数据相关叠加训练的信道估计的最优导频设计
本文提出了一种新的数据依赖叠加训练技术,用于由单/多载波(SC/MC)和加零/循环前缀(CP)系统组成的通用块传输(BT)系统的信道估计。所述训练序列包括已知训练序列和接收器不知道的数据相关序列的总和。该方案的独特之处在于信道估计不受使用数据相关序列的影响。该导频设计框架是为了最小化与信道估计误差相关的贝叶斯cram - rao界(BCRB)。仿真结果显示了该方案在单载波和多载波加零和循环前缀系统中的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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