A Low-Complexity Path Delay Searching Method in Sparse Channel Estimation for OFDM Systems

Kee-Hoon KIM  

Publication
IEICE TRANSACTIONS on Communications   Vol.E101-B   No.11   pp.2297-2303
Publication Date: 2018/11/01
Online ISSN: 1745-1345
DOI: 10.1587/transcom.2018EBP3026
Type of Manuscript: PAPER
Category: Wireless Communication Technologies
Keyword: 
channel estimation,  compressed sensing (CS),  low-complexity,  low pass filter (LPF),  orthogonal frequency division multiplexing (OFDM),  

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Summary: 
By exploiting the inherent sparsity of wireless channels, the channel estimation in an orthogonal frequency division multiplexing (OFDM) system can be cast as a compressed sensing (CS) problem to estimate the channel more accurately. Practically, matching pursuit algorithms such as orthogonal matching pursuit (OMP) are used, where path delays of the channel is guessed based on correlation values for every quantized delay with residual. This full search approach requires a predefined grid of delays with high resolution, which induces the high computational complexity because correlation values with residual at a huge number of grid points should be calculated. Meanwhile, the correlation values with high resolution can be obtained by interpolation between the correlation values at a low resolution grid. Also, the interpolation can be implemented with a low pass filter (LPF). By using this fact, in this paper we substantially reduce the computational complexity to calculate the correlation values in channel estimation using CS.