Model-Based Compressive Channel Estimation over Rapidly Time-Varying Channels in OFDM Systems
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- LIU Yi
- School of Information and Electronics, Beijing Institute of Technology Department of Information Technology, College of National Defense Information Science
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- MEI Wenbo
- School of Information and Electronics, Beijing Institute of Technology
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- DU Huiqian
- School of Information and Electronics, Beijing Institute of Technology
説明
By exploiting the inherent sparsity of wireless propagation channels, the theory of compressive sensing (CS) provides us with novel technologies to estimate the channel state information (CSI) that require considerably fewer samples than traditional pilot-aided estimation methods. In this paper, we describe the block-sparse structure of the fast time-varying channel and apply the model-based CS (MCS) for channel estimation in orthogonal frequency division multiplexing (OFDM) systems. By exploiting the structured sparsity, the proposed MCS-based method can further compress the channel information, thereby allowing a more efficient and precise estimation of the CSI compared with conventional CS-based approaches. Furthermore, a specific pilot arrangement is tailored for the proposed estimation scheme. This so-called random grouped pilot pattern can not only effectively protect the measurements from the inter-carrier interference (ICI) caused by Doppler spreading but can also enable the measurement matrix to meet the conditions required for MCS with relatively high probability. Simulation results demonstrate that our method has good performance at high Doppler frequencies.
収録刊行物
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- IEICE Transactions on Communications
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IEICE Transactions on Communications E97.B (8), 1709-1716, 2014
一般社団法人 電子情報通信学会
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詳細情報 詳細情報について
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- CRID
- 1390001204376896256
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- NII論文ID
- 130004679238
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- ISSN
- 17451345
- 09168516
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- Crossref
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可