（信息科學與技術國家實驗室,清華大學 北京100084）

摘要：本文研究基于壓縮感知的多徑信道估計方法。多徑信道往往呈現明顯的稀疏特性，適合應用壓縮感知技術進行處理。本文分析比較了傳統的線性估計算法－最小二乘法與多種壓縮感知算法(Lasso、CoSaMP和IHT)在多徑信道估計上的性能差異，并提出一種基于迭代型偽逆的高效信道估計方法，該方法與經典的壓縮感知算法相比，在恢復精度、時間復雜度和恢復成功率方面有明顯的性能提升。
關鍵詞：信道估計；壓縮感知
中圖分類號：□□□□□        文獻標識碼：A        文章編號：

                       Study on Channel Estimation based on Compressive Sensing
                                       QI Ting, WEN Ke, WANG You-zheng
　�。═singhua National Laboratory for Information Science and Technology (TNList), Tsinghua University,
Beijing 100084, P. R. China. Correspondence Address: WANG You-zheng: yzhwang@tsinghua.edu.cn）
Abstract：In this paper, the channel estimation of multi-path transmission, which usually shows sparse features, is studied by compressive sensing. It is compared between traditional linear algorithm, such as Least Square (LS), and several compressive sensing methods, including Lasso, CoSaMP and IHT algorithms. We propose an efficient algorithm based on iterative pseudo-inverse and compare it with typical compressive sensing methods. It is observed that the performance of the proposed algorithm is obviously improved in terms of restoration precision, time complexity and success rate of recovery.
Key words：Channel Estimation；Compressive Sensing

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