| 摘要: |
| 给出了一种新的聚类估计最大似然序列均衡器(CBSE),避开了传统MLSE均衡需要估计信道脉冲响应(CIR)和卷积运算,由接收信号估计聚类中心,同时利用聚类中心之间的对称性,仅需估计其中部分中心,其余中心可通过简单运算获取,从而在缩短训练序列的同时减少了运算量.仿真表明,新方法在取得与RLS均衡器相近收敛性能的同时,计算量比LMS均衡器小. |
| 关键词: 信道均衡 信道估计 聚类 最大似然序列估计 |
| DOI：10.3969/j.issn.1001-893X. |
| 投稿时间：2006-10-12修订日期：2007-04-20 |
| 基金项目:军队预先研究项目 |
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| A Low-Complexity Cluster Estimation for MLSE Equalizers |
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| Abstract: |
| A new cluster-based Maximum Likelihood Sequence Equalizer(CBSE)is presented.The novel algorithm avoids the problem of the parametric estimation of the channel impulse response(CIR)and convolutions,which is required by the MLSE equalizers.By exploiting the symmetries existing among the clusters formed by the received data sequence,only parts of the cluster centers need to be estimated,and the rest are computed via simple operations.This reduces dramatically both the computational complexity and the required length of the training sequence.Simulations show that its overall complexity is lower than that of the LMS-based MLSE equalizer,with an RLS-like performance. |
| Key words: channel equalization channel estimation clustering MLSE |
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