针对突发脉冲噪声，提出改进的盲信道估计算法，收敛更快且更准确。
Robust Blind Channel Estimation for Bursty Impulsive Noise with a Constrained EM Approach
- 利用脉冲噪声的马尔可夫-梅顿模型和BPSK符号结构设计约束EM算法
- 收敛速度接近标准EM的两倍，估计性能更优
- 适合高敏感无线接收场景中抗脉冲噪声的信道估计
由电力设备产生的脉冲噪声（IN）会严重降低高灵敏度无线接收机的性能。获取精确的信道状态信息（CSI）是设计最优最大后验检测器的关键。本文研究了基于期望最大化（EM）算法的盲信道估计算法，适用于受突发脉冲噪声影响的场景，该噪声可用马尔可夫-梅顿模型描述。提出一种约束型EM算法，利用脉冲噪声模型的格状结构及传输的二进制相移键控（BPSK）符号特性。通过在特定格状状态间施加共享方差，并对转移矩阵施加对称性约束，所提出的约束型EM算法在突发脉冲噪声信道下，收敛速率几乎为标准EM方法的两倍，且估计性能更优。我们全面评估了标准与约束型EM估计器在不同类型CSI不确定性下的鲁棒性。结果表明，两种EM估计器的最终估计均能有效抵抗马尔可夫-梅顿模型参数失配；然而，随着CSI不确定性水平升高，收敛速率下降。
原文摘要 · Abstract (English)
Impulsive noise (IN) commonly generated by power devices can severely degrade the performance of high sensitivity wireless receivers. Accurate channel state information (CSI) knowledge is essential for designing optimal maximum a posteriori detectors. This paper examines blind channel estimation methods based on the expectation-maximization (EM) algorithm tailored for scenarios impacted by bursty IN, which can be described by the Markov-Middleton model. We propose a constrained EM algorithm that exploits the trellis structure of the IN model and the transmitted binary phase shift keying (BPSK) symbols. By enforcing shared variance among specific trellis states and symmetry in the transition matrix, the proposed constrained EM algorithm adapted for the bursty IN channel has an almost two times faster convergence rate and better estimation performance than the standard EM approach. We comprehensively evaluate the robustness of both standard and constrained EM estimators under different types of CSI uncertainties. The results indicate that the final estimations of both EM estimators are robust enough to mismatch Markov-Middleton model parameters. However, as the level of CSI uncertainty increases, the convergence rate decreases.
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