The objective function for protection class C k can be expressed as max λ C z ∑ j = 1 N s C z ∑ i = 2 d v max C z λ M j, i C z, C k. (14).
The problem can be expressed as: max p i { 1 - P d P H 1 + P f P H 0 }, subject to u 2 i = u 1 i, u 3 i = u 0 i. (13).
Then, the problem of waveform design can be expressed as max s log det I M + R H S H S s. t. tr S H S p 1 / p ≤ J, (8).
In the same way, the computational complexity of T-MUSIC can be expressed as max (O (M3), O (htM2)), where h t is the number of searches conducted along the time delay axis.
Therefore, a sum rate maximization problem with power constraints can be expressed as max ∑ k log I + H k T k T k H H k H s. t. tr T k T k H ≤ P k, k = 1, …, K H ˜ k T k = 0, k = 1, …, K (4).
Let D = X H X. Since U is unitary, tr(S H S) = tr(X H X). Now the problem formulation can be expressed as max D log det I M + Λ D s. t. tr D p 1 / p ≤ J. (11).
Furthermore, since Q x) is a monotonically decreasing function of x, we can transform (P3) into a linear programming problem, which is expressed as: max λ ∑ n = 1 N KL λ n δ 2 − 1 Π 0 R n 0 P ( 0 ), ρ ( 0 ) + ∑ n = 1 N KL 1 + 2 γ n λ n δ 2 − 1 − γ n Π 1 R n 1 P ( 0 ), ρ ( 0 ), s.t.
The problem of finding the covariance matrices K2,1 and K2,2 that maximize the secondary rate under the aforementioned constraints is expressed as max K 2, 1, K 2, 2 R 2 und (10a) subject to: R 1 und ≥ R 1 ⋆, (10b) R 1, 2 und ≥ R 1 ⋆, (10c) tr { K 2, 1 + K 2, 2 } ≤ P 2, (10d) K 2, 1 ≽ 0, K 2, 2 ≽ 0, (10,).
The maximum number of M2M packets r that can be multiplexed into a large IP packet can be expressed as, r = frac{n_{max} - additional Un protocol overhead}{l}, (3).
The user selection criterion can be expressed as min V max i, j ∈ V ; i ≠ j ∣ H i H j H ∣, (5).
The estimated maximum and minimum of multivariable function d f, dmax and dmin, can be expressed as d max = max ( d emax, d fimax ), (25) d min = min ( d emin, d fimin ).
