Bounds and Algorithms for Multiple Frequency Offset Estimation in Cooperative Networks
Bounds and Algorithms for Multiple Frequency Offset Estimation in Cooperative Networks
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DOI：
10.1109/twc.2011.030311.101184
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发表时间：
2011-03
影响因子：
10.4
通讯作者：
H. Mehrpouyan;S. Blostein
中科院分区：
文献类型：
--
作者：
H. Mehrpouyan;S. Blostein
协作网络的分布式特性可能导致多载波频率偏移（CFO），这使得信道时变，并掩盖了协作通信所承诺的分集增益。本文旨在解决空分多址（SDMA）合作网络中使用训练序列的多个CFO估计。系统模型和CFO估计问题的情况下，解码和转发（DF）和放大和转发（AF）中继制定和新的封闭形式的Cramer-Rao下界（CRLB）的表达式推导出这两个协议。CRLB，然后以一种新的方式来制定训练序列的设计准则，并确定网络协议和拓扑结构的CFO估计的效果。接下来，提出了两个计算效率高的迭代估计，确定从多个同时中继节点的CFO。所提出的算法在不牺牲带宽和训练性能的情况下降低了多频偏估计的复杂度。与现有的多个CFO估计器不同，所提出的估计器对于大CFO值和小CFO值都是准确的。数值结果表明，新方法的性能优于现有的算法，达到或接近CRLB在中高信噪比（SNR）。仿真结果表明，该估计器用于系统补偿时，能显著降低系统的平均误码率。
The distributed nature of cooperative networks may result in multiple carrier frequency offsets (CFOs), which make the channels time varying and overshadow the diversity gains promised by collaborative communications. This paper seeks to address multiple CFO estimation using training sequences in space-division multiple access (SDMA) cooperative networks. The system model and CFO estimation problem for cases of both decode-and-forward (DF) and amplify-and-forward (AF) relaying are formulated and new closed-form expressions for the Cramer-Rao lower bound (CRLB) for both protocols are derived. The CRLBs are then applied in a novel way to formulate training sequence design guidelines and determine the effect of network protocol and topology on CFO estimation. Next, two computationally efficient iterative estimators are proposed that determine the CFOs from multiple simultaneously relaying nodes. The proposed algorithms reduce multiple CFO estimation complexity without sacrificing bandwidth and training performance. Unlike existing multiple CFO estimators, the proposed estimators are also accurate for both large and small CFO values. Numerical results show that the new methods outperform existing algorithms and reach or approach the CRLB at mid-to-high signal-to-noise ratio (SNR). When applied to system compensation, simulation results show that the proposed estimators significantly reduce average-bit-error-rate (ABER).