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Article Navigation >  Journal of University of Electronic Science and Technology of China  > 2013  >  42(1): 58-62

WANG Ni-na, GUI Guan, SU Yong-tao, SHI Jing-lin, ZHANG Ping. Compressive Sensing-Based Sparse Channel Estimation Method for MIMO-OFDM Systems[J]. Journal of University of Electronic Science and Technology of China, 2013, 42(1): 58-62. doi: 10.3969/j.issn.1001-0548.2013.01.014
Citation: WANG Ni-na, GUI Guan, SU Yong-tao, SHI Jing-lin, ZHANG Ping. Compressive Sensing-Based Sparse Channel Estimation Method for MIMO-OFDM Systems[J]. Journal of University of Electronic Science and Technology of China, 2013, 42(1): 58-62. doi: 10.3969/j.issn.1001-0548.2013.01.014
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Compressive Sensing-Based Sparse Channel Estimation Method for MIMO-OFDM Systems

doi: 10.3969/j.issn.1001-0548.2013.01.014
  • 1.

    Institute of Computing Technology,Chinese Academy of Sciences Haidian Beijing 100190;

  • 2.

    Beijing Key Laboratory of Mobile Computing and Pervasive Device Haidian Beijing 100190;

  • 3.

    School of Information and Communication Engineering,Beijing University of Posts and Telecommunications Haidian Beijing 100876;

  • 4.

    School of Electronic and Engineering,University of Electronic Science and Technology of China Chengdu 611731

  • Received Date: 2011-05-04
  • Rev Recd Date: 2012-03-07
  • Publish Date: 2013-02-15
  • Channel equalization and coherent detection require accurate channel state information (CSI) at the receiver for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. The conventional linear recovery methods, such as least squares (LS) and minimum mean square error (MMSE), are widely adapted in channel estimation under the assumption of rich multipath. However, numerous physical measurements have verified that the practical multipath channels tend to exhibit sparse structures. In this paper, exploiting the channel sparsity, we propose a compressive sensing-based CoSaMP recovery algorithm for MIMO-OFDM sparse channel estimation. Simulations show that the compressive sensing estimation method can obtain the accurate CSI with fewer pilots than conventional linear estimation for MIMO-OFDM systems at the cost of less computational complexity. The proposed method can greatly improve the spectrum efficiency for MIMO-OFDM systems.
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  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

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Compressive Sensing-Based Sparse Channel Estimation Method for MIMO-OFDM Systems

doi: 10.3969/j.issn.1001-0548.2013.01.014
  • 1. Institute of Computing Technology,Chinese Academy of Sciences Haidian Beijing 100190;
  • 2. Beijing Key Laboratory of Mobile Computing and Pervasive Device Haidian Beijing 100190;
  • 3. School of Information and Communication Engineering,Beijing University of Posts and Telecommunications Haidian Beijing 100876;
  • 4. School of Electronic and Engineering,University of Electronic Science and Technology of China Chengdu 611731
  • Received Date: 2011-05-04
  • Rev Recd Date: 2012-03-07
  • Publish Date: 2013-02-15

Abstract: Channel equalization and coherent detection require accurate channel state information (CSI) at the receiver for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. The conventional linear recovery methods, such as least squares (LS) and minimum mean square error (MMSE), are widely adapted in channel estimation under the assumption of rich multipath. However, numerous physical measurements have verified that the practical multipath channels tend to exhibit sparse structures. In this paper, exploiting the channel sparsity, we propose a compressive sensing-based CoSaMP recovery algorithm for MIMO-OFDM sparse channel estimation. Simulations show that the compressive sensing estimation method can obtain the accurate CSI with fewer pilots than conventional linear estimation for MIMO-OFDM systems at the cost of less computational complexity. The proposed method can greatly improve the spectrum efficiency for MIMO-OFDM systems.

WANG Ni-na, GUI Guan, SU Yong-tao, SHI Jing-lin, ZHANG Ping. Compressive Sensing-Based Sparse Channel Estimation Method for MIMO-OFDM Systems[J]. Journal of University of Electronic Science and Technology of China, 2013, 42(1): 58-62. doi: 10.3969/j.issn.1001-0548.2013.01.014
Citation: WANG Ni-na, GUI Guan, SU Yong-tao, SHI Jing-lin, ZHANG Ping. Compressive Sensing-Based Sparse Channel Estimation Method for MIMO-OFDM Systems[J]. Journal of University of Electronic Science and Technology of China, 2013, 42(1): 58-62. doi: 10.3969/j.issn.1001-0548.2013.01.014
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