For Full-Text PDF, please login, if you are a member of IEICE,|
or go to Pay Per View on menu list, if you are a nonmember of IEICE.
Model-Based Compressive Channel Estimation over Rapidly Time-Varying Channels in OFDM Systems
Yi LIU Wenbo MEI Huiqian DU
IEICE TRANSACTIONS on Communications
Publication Date: 2014/08/01
Online ISSN: 1745-1345
Type of Manuscript: PAPER
Category: Wireless Communication Technologies
model-based compressive sensing, channel estimation, OFDM, block-sparse model, rapidly time-varying channel,
Full Text: PDF(1006.6KB)>>
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.