Blind Channel Estimation for Amplify-and-Forward Two-Way Relay Networks Employing $M$ -PSK Modulation
Blind Channel Estimation for Amplify-and-Forward Two-Way Relay Networks Employing $M$ -PSK Modulation
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DOI：
10.1109/tsp.2012.2193577
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发表时间：
2011-01
影响因子：
5.4
通讯作者：
S. Abdallah;I. Psaromiligkos
中科院分区：
文献类型：
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作者：
S. Abdallah;I. Psaromiligkos
研究了放大转发（AF）双向中继网络（TWRNs）的信道估计问题。大多数关于这个问题的工作都集中在基于飞行员的方法上，这种方法增加了大量的训练开销，降低了系统的频谱效率。为了避免这种损失，我们提出了采用恒模（CM）信令的AF TWRNs的盲信道估计算法。我们的主要算法是基于确定性最大似然（DML）方法。假设M -PSK调制，我们证明了所得估计量是一致的，并且在调制阶数高于2的高信噪比下以高概率接近真信道。然而，对于BPSK， DML算法表现不佳，我们提出了一种替代算法，通过考虑数据符号的BPSK结构，该算法可以产生更好的性能。为了比较，我们还研究了高斯最大似然（GML）方法，该方法将数据符号视为高斯分布的干扰参数。我们推导了Cramer-Rao界，并使用蒙特卡罗模拟来研究所提出算法的均方误差（MSE）性能。我们还比较了DML算法的符号错误率（SER）性能与基于训练的最小二乘（LS）算法的性能，并证明DML在精度和频谱效率之间提供了更好的权衡。
We consider the problem of channel estimation for amplify-and-forward (AF) two-way relay networks (TWRNs). Most works on this problem focus on pilot-based approaches which impose a significant training overhead that reduces the spectral efficiency of the system. To avoid such losses, we propose blind channel estimation algorithms for AF TWRNs that employ constant-modulus (CM) signaling. Our main algorithm is based on the deterministic maximum likelihood (DML) approach. Assuming M -PSK modulation, we show that the resulting estimator is consistent and approaches the true channel with high probability at high SNR for modulation orders higher than 2. For BPSK, however, the DML algorithm performs poorly and we propose an alternative algorithm that yields much better performance by taking into account the BPSK structure of the data symbols. For comparative purposes, we also investigate the Gaussian maximum-likelihood (GML) approach which treats the data symbols as Gaussian-distributed nuisance parameters. We derive the Cramer-Rao bound and use Monte Carlo simulations to investigate the mean squared error (MSE) performance of the proposed algorithms. We also compare the symbol-error rate (SER) performance of the DML algorithm with that of the training-based least-squares (LS) algorithm and demonstrate that the DML offers a superior tradeoff between accuracy and spectral efficiency.