Super-Resolution Sparse MIMO-OFDM Channel Estimation Based on Spatial and Temporal Correlations
July 20, 2015 Β· Declared Dead Β· π IEEE Communications Letters
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Authors
Zhen Gao, Linglong Dai, Zhaohua Lu, Chau Yuen, Zhaocheng Wang
arXiv ID
1507.05441
Category
cs.IT: Information Theory
Citations
81
Venue
IEEE Communications Letters
Last Checked
5 months ago
Abstract
This letter proposes a parametric sparse multiple input multiple output (MIMO)-OFDM channel estimation scheme based on the finite rate of innovation (FRI) theory, whereby super-resolution estimates of path delays with arbitrary values can be achieved. Meanwhile, both the spatial and temporal correlations of wireless MIMO channels are exploited to improve the accuracy of the channel estimation. For outdoor communication scenarios, where wireless channels are sparse in nature, path delays of different transmit-receive antenna pairs share a common sparse pattern due to the spatial correlation of MIMO channels. Meanwhile, the channel sparse pattern is nearly unchanged during several adjacent OFDM symbols due to the temporal correlation of MIMO channels. By simultaneously exploiting those MIMO channel characteristics, the proposed scheme performs better than existing state-of-the-art schemes. Furthermore, by joint processing of signals associated with different antennas, the pilot overhead can be reduced under the framework of the FRI theory.
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