Let A be a deterministic N×N complex matrix.
Let A be a deterministic N×N complex matrix with bounded spectral norm.
[[18], Lemma 1] Let A be a deterministic n×n complex matrix with uniformly bounded spectral radius for all n.
In recent works, deconvolution, based on the moments method, has been analyzed when n → ∞ for some particular matrices A and B. For instance, when A is a random Vandermonde matrix and B is a deterministic diagonal matrix [43], or when A and B are two independent random Vandermonde matrices [44].
The matrix H μ is a deterministic mean matrix which represents the LOS component and satisfies T r ( H μ H μ H ) = N R N T, (3).
where might be a deterministic function of.
Let G = (V,E) be a deterministic network.
The overcomplete basis matrix A =[a ϕ1),..., a (ϕ K )] is a deterministic basis matrix under this condition, where the vector a(ϕ k ) denotes the array steering vector and ϕ k is the k th sampling grid.
where G ∈ C N o × R g is a preamble matrix with pseudo-random entries and P ( O ) ∈ C N o × R p ( O ) is a deterministic pilot matrix, known a priori by the frame generator.
Fortunately, the above issue can be alleviated by utilizing a deterministic matrix F since it can be constructed and stored in FC beforehand and its transmission becomes unnecessary.
