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Proposition 2. The marginal CDF of can be alteratively expressed as (15).
The marginal CDF of the largest eigenvalue (i.e., ) of the double-scattering channel matrix was reported earlier in [14].
Given that the ordered eigenvalues of are jointly distributed as (5), the marginal CDF of the th largest eigenvalue can be expressed as (18).
If the joint PDF of the ordered eigenvalues is given by (1), the marginal CDF of the th largest eigenvalue can be expressed as (13).
According to [60, Equation ], the marginal CDF of the th largest variable can be expressed as (note that [60, Equation ] deals with random variables in ascendent order. However, the result there can be easily rewritten to cover the descending-order cases by appropriate change of variables) (B6).
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Figure 1 Marginal CDFs of ordered eigenvalues of when,, and.
We also note that marginal CDFs of the ordered eigenvalues were also investigated in the authors' previous work [47].
where F s(s) and F n(n) are the marginal CDFs of the faded signal and noise, and θ c is the dependence parameter in the copula density function.
(f_{q_{_{k1}}'}left (q_{_{k1}}'right)) and (f_{q_{_{k2}}'}left (q_{_{k2}}'right)) are the marginal CDFs of the signals (q'_{_{k1}}left (tright)) and (q'_{_{k2}}left (tright)), respectively, and ρ k is the linear correlation parameter between these two signals.
We derive a new approximation of the post-processing SNR inverse marginal CDF through an approximation of the marginal CDF for ordered eigenvalues in Wishart random matrices.
By the definition of marginal CDF, we have (16).
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