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In this paper, the joint pilot placement and symbol design optimization problem for sparse CE in OFDM systems is considered based on minimizing the mutual coherence of the Fourier submatrix associated with the pilot subcarriers.
A uniform elemental power constraint is adopted as the optimization criterion is to minimize the mutual coherence of the sensing matrix using a sparse model and to achieve high-resolution estimation in both range and angle dimensions.
Here, too, an objection has been raised: namely that art is not wholly indifferent to historical criteria, because it obeys the laws of "verisimilitude"; but, here again, "verisimilitude" is only a rather clumsy metaphor for the mutual coherence of images, which without this internal coherence would fail to produce their effect as images, like Horace's delphinus in silvis and aper in fluctibus.
Therefore, the mutual coherence of measurement matrix in DCS-based channel estimation for MIMO-OFDM system consists of mutual coherence of different SISO-OFDM systems two by two.
Our criteria depend on the notion of mutual coherence of a dictionary.
The mutual coherence of the measurement matrix is considered as the fitness function in this paper.
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It is caused by the impact of mutual coherence on the mean square error of estimation in DCS-based approaches which is addressed in the literature.
Consequently, the mutual coherence for both of the matrices are the same and row-wise permutation does not change the mutual coherence.
On the other hand, we assume (bar {boldsymbol {Phi }} = left [ phi _{1}; phi _{3}; phi _{2}; ldots ; phi _{n} right ]), then mutual coherence for both of the measurement matrices can be calculated as the maximum off-diagonal entry of (sum _{i = 1}^{n}phi _{i}^{H}phi _{i}).
The filter transfer function is given by the mutual coherence function of the filtered source which allows, through an inverse problem, sculpting the RF filter response.
These recovery results depend on the mutual coherence μ of the system.
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