OFDM系统中基于压缩传感理论的信道估计算法 |
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引用本文: | 陈书贞,张亚静,练秋生. OFDM系统中基于压缩传感理论的信道估计算法[J]. 信号处理, 2010, 26(1): 157-160 |
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作者姓名: | 陈书贞 张亚静 练秋生 |
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作者单位: | 燕山大学信息科学与工程学院 |
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摘 要: | 信道估计是OFDM系统中的一项关键技术,信道估计质量的好坏对整个系统的性能有重要的影响。传统的最小均方算法对稀疏信道进行估计时存在精确性差的缺陷。本文利用信道冲激响应的稀疏性,提出了一种基于近似l0范数的信道估计算法。该算法用三种函数逼近l0范数,应用梯度下降法和梯度投影算法获得代价函数的最优解,从而得到信道的最稀疏解。仿真实验结果表明:在相同条件下,与基于l1范数的信道估计算法比较,本文算法的收敛速度快,估计值信噪比高,且均方误差小。
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关 键 词: | OFDM 稀疏信道 压缩传感 l0范数 |
收稿时间: | 2009-01-07 |
Channel estimation algorithm based on compressed sensing for OFDM systems |
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Affiliation: | The college of Information Science and Engineering,Yanshan University,Qinhuangdao Hebei |
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Abstract: | Channel estimation for orthogonal frequency division multiplexing (OFDM) is a crucial technology.The quality of channel estimation has vital impact on the overall system performance.The traditional channel based on linear minimum mean-squared error suffers low accuracy.Exploiting the sparsity of channel impulse response,a channel estimation algorithm based on approximately?l0 norm is proposed.We use three functions to approximate l0 norm,and get the optimal solution of the cost function by applying gradient descend and gradient projection algorithm,thus obtains the sparsest channel response.Simulated experiment results show that under the same conditions,compared with the channel estimation algorithm based on l1 norm,the proposed algorithm’s convergence speed is faster,and the signal-to-noise ratio is higher. |
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Keywords: | OFDM orthogonal frequency division multiplexing (OFDM) sparse channel compressed sensing l0 norm |
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