SCIENCE CHINA Information Sciences, Volume 60 , Issue 8 : 082303(2017) https://doi.org/10.1007/s11432-016-0386-x

## Compressed sensing-based time-domain channel estimator for full-duplex OFDM systems with IQ-imbalances

• AcceptedNov 9, 2016
• PublishedMar 6, 2017
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### Acknowledgment

This work was supported in part by National Natural Science Foundation of China (Grant Nos. 61271230, 61472190, 6147210, 61501238), Open Research Fund of National Key Laboratory of Electromagnetic Environment, China Research Institute of Radiowave Propagation (Grant No. 201500013), Open Research Fund of National Mobile Communications Research Laboratory, Southeast University (Grant No. 2013D02), and Research Fund for Doctoral Program of Higher Education of China (Gant No. 20113219120019)

• Figure 1

Full-duplex system model with IQ-imbalance.

• Figure 2

Block diagram of the proposed adaptive OMP algorithm.

• Figure 3

Curves of the BER versus the $\beta$ of the GP in [22]with three different SNRs.

• Figure 4

Curves of the BER vesus the $\gamma$ of the proposed adaptive OMP with three different SNRs.

• Figure 5

Curves of the BER versus the SNRs of different channel estimators.

• Figure 6

Curves of the MSE versus the SNRs of different channel estimators.

•

Algorithm 1 Proposed adaptive OMP algorithm

Require:$\boldsymbol{A}$, $\boldsymbol{z}$

Output:$\hat{\boldsymbol{\tilde{x}}}$ [\bfseries~Initialization:] $K=0$

[\bfseries~Steps:]

Compute $\boldsymbol{\hat{\tilde{x}}}$ using (40) and estimate $\hat{\sigma}_w^2$ using (41).

Set the nice threshold $\gamma$ by simulation.

Estimate the $K$-sparsity for the OMP using (42).

Call the OMP method in [26] to obtain the sparse version of $\boldsymbol{x}$ in (sys_mod_m_pos).

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