Superimposed Training Based Channel Estimation for OFDM Modulated Amplify-and-Forward Relay Networks
Superimposed Training Based Channel Estimation for OFDM Modulated Amplify-and-Forward Relay Networks
复制标题
基于叠加训练的 OFDM 调制放大转发中继网络信道估计
DOI：
10.1109/tcomm.2011.051711.100431
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发表时间：
2011-05
影响因子：
8.3
通讯作者：
Xian-Da Zhang
中科院分区：
文献类型：
--
作者：
Feifei Gao;B Jiang;X.-Q. Gao;Xian-Da Zhang
本文研究了采用放大转发（AF）传输方案和正交频分复用（OFDM）调制的经典三节点中继网络的信道估计问题。我们提出了一种叠加训练策略，允许目的节点分别获取源→中继链路和中继→目的链路的信道信息。具体来说，中继器将自己的训练信号叠加在接收到的训练信号上，然后将其转发到目的地。所提出的训练策略可以在两个传输阶段内实现，因此与两阶段数据传输方案相兼容，即可以将训练嵌入到数据传输中。我们还推导了随机信道参数的cram<s:1> r- rao界，并以此计算了最优训练序列和最优功率分配。由于最优最小均方误差（MMSE）估计量和最大后验误差（MAP）估计量不能用封闭形式表示，我们提出首先从线性最小均方误差（LMMSE）和最小二乘（LS）估计量等低复杂度线性估计量中获得初始信道估计，然后采用迭代方法提高估计精度。仿真结果证实了所提出的研究。
In this paper, we consider the channel estimation for the classical three-node relay networks that employ the amplify-and-forward (AF) transmission scheme and the orthogonal frequency division multiplexing (OFDM) modulation. We propose a superimposed training strategy that allows the destination node to separately obtain the channel information of the source→relay link and the relay→destination link. Specifically, the relay superimposes its own training signal over the received one before forwarding it to the destination. The proposed training strategy can be implemented within two transmission phases and is thus compatible with the two-phase data transmission scheme, i.e., the training can be embedded into data transmission. We also derive the Cramér-Rao bound for the random channel parameters, from which we compute the optimal training sequence as well as the optimal power allocation. Since the optimal minimum mean square error (MMSE) estimator and the maximum a posteriori (MAP) estimator cannot be expressed in closed-form, we propose to first obtain the initial channel estimates from the low complexity linear estimators, e.g., linear minimum mean-square error (LMMSE) and least square (LS) estimators, and then resort to the iterative method to improve the estimation accuracy. Simulation results are provided to corroborate the proposed studies.
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影响因子：
2.6
作者：
K. Yan;Sheng Ding;Yunzhou Qiu;Yingguan Wang;Haitao Liu
通讯作者：
K. Yan;Sheng Ding;Yunzhou Qiu;Yingguan Wang;Haitao Liu
DOI：
10.1109/twc.2006.1633369
发表时间：
2004-11
期刊：
IEEE Global Telecommunications Conference, 2004. GLOBECOM '04.
影响因子：
--
作者：
H. Minn;N. Al-Dhahir
通讯作者：
H. Minn;N. Al-Dhahir
影响因子：
5.4
作者：
A. Vosoughi;A. Scaglione
通讯作者：
A. Vosoughi;A. Scaglione
影响因子：
5.4
作者：
Y. Rong;Xiaojun Tang;Y. Hua
通讯作者：
Y. Rong;Xiaojun Tang;Y. Hua
DOI：
10.1109/lcomm.2010.100810.101441
发表时间：
2010-11
期刊：
IEEE Communications Letters
影响因子：
--
作者：
Moon-Gun Song;Dongsik Kim;G. Im
通讯作者：
Moon-Gun Song;Dongsik Kim;G. Im