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基于Golay互補(bǔ)序列的壓縮感知稀疏信道估計(jì)算法

姚志強(qiáng),  李廣龍,  王仕果,  游志宏

姚志強(qiáng), 李廣龍, 王仕果, 游志宏. 基于Golay互補(bǔ)序列的壓縮感知稀疏信道估計(jì)算法[J]. 電子與信息學(xué)報(bào), 2016, 38(2): 282-287. doi: 10.11999/JEIT150594
引用本文: 姚志強(qiáng), 李廣龍, 王仕果, 游志宏. 基于Golay互補(bǔ)序列的壓縮感知稀疏信道估計(jì)算法[J]. 電子與信息學(xué)報(bào), 2016, 38(2): 282-287. doi: 10.11999/JEIT150594
YAO Zhiqiang, LI Guanglong, WANG Shiguo, YOU Zhihong. Compressed Sensing Channel Estimation Algorithm Based on Deterministic Sensing with Golay Complementary Sequences[J]. Journal of Electronics & Information Technology, 2016, 38(2): 282-287. doi: 10.11999/JEIT150594
Citation: YAO Zhiqiang, LI Guanglong, WANG Shiguo, YOU Zhihong. Compressed Sensing Channel Estimation Algorithm Based on Deterministic Sensing with Golay Complementary Sequences[J]. Journal of Electronics & Information Technology, 2016, 38(2): 282-287. doi: 10.11999/JEIT150594

基于Golay互補(bǔ)序列的壓縮感知稀疏信道估計(jì)算法

doi: 10.11999/JEIT150594
基金項(xiàng)目: 

國(guó)家自然科學(xué)基金(61372127)，湖南省自然科學(xué)基金(13JJ3065)

Compressed Sensing Channel Estimation Algorithm Based on Deterministic Sensing with Golay Complementary Sequences

Funds: 

The National Natural Science Foundation of China (61372127), The Natural Science Foundation of Hunan Province (13JJ3065)

  • 摘要: 該文針對(duì)現(xiàn)有基于壓縮感知的信道估計(jì)方法峰均功率比高、計(jì)算量大等問(wèn)題，使用確定性格雷(Golay)序列作為訓(xùn)練序列對(duì)稀疏信道進(jìn)行信道估計(jì)，在接收端實(shí)現(xiàn)了對(duì)信道沖激響應(yīng)的估計(jì)，給出了估計(jì)模型和具體的算法推演，推導(dǎo)了該方法的峰均功率比，并與基于隨機(jī)高斯序列的壓縮感知信道估計(jì)方法的性能、峰均功率比和計(jì)算量進(jìn)行了比較。仿真實(shí)驗(yàn)表明：格雷序列以及隨機(jī)高斯序列兩種序列都可以重構(gòu)出稀疏信道非零抽頭系數(shù)，但是格雷序列對(duì)稀疏信道沖激響應(yīng)的確定性觀測(cè)估計(jì)值的均方誤差(MSE)和匹配度性能(Match Rate, MR)均優(yōu)于隨機(jī)高斯序列，計(jì)算量降低了許多，且在OFDM系統(tǒng)中峰均功率比大大降低。
    Abstract: To deal with problems of large Peak-to-Average Power Ratio (PAPR) and computation complexity in existing channel estimation algorithm based on compressed sensing, Golay complementary sequence is utilized to estimate sparse channel as a deterministic training sequence. Estimation model and algorithm are provided in detail. The PAPR of this method is deduced and its performance, PAPR and computation complexity are compared with Gaussian random sequence. The simulation result indicates that Golay sequence and Gaussian random sequence can reconstruct nonzero tap coefficients. But Golay sequence outperforms Gaussian random sequence both in the Mean Square Error (MSE) and Match Rate (MR) for estimating sparse channel impulse response. And the computation and PAPR are reduced significantly in the OFDM system.
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出版歷程
  • 收稿日期:  2015-05-18
  • 修回日期:  2015-09-16
  • 刊出日期:  2016-02-19

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