Sentence examples for modeled as complex from inspiring English sources

for, where is the time-delay of the signal, and represent, respectively, the channel coefficient and the CFO for the signal in the th branch, is the baseband representation of the transmitted signal in the th band, and is modeled as complex white Gaussian noise with independent components, each having spectral density.

We assume that all nodes have the same average power constraint P watts and transmission bandwidth W Hz. While this model has been well-studied in the case of static flat channels [21], here the links between the nodes are assumed to be frequency selective quasi-static fading channels, modeled as complex FIR filters.

We further assume that channels h m ( k, t ) and g k ( t ), m=1,…,M and k=1,…,K, are Rayleigh fading channel gains (modeled as complex Gaussian with zero mean and unit variance), and they change independently over different time channel uses.

The vector x 0 that contain the data symbols at the source is modeled as complex random variables with covariance matrix (mathbf {R}_{x_{0}}=mathsf {E}left {mathbf {x_{0}} mathbf {x_{0}}^{H}right }) under the power constraint (mathsf {tr}{mathbf {R}_{x_{0}}}=P_{0}).

All noise terms in (3) to (5) are the additive white Gaussian noise (AWGN) components modeled as complex random variables with zero mean and variance of N 0/2 per dimension.

The N δmax+T+1)×N noise vector n D [i] contains the equivalent received noise vector at the destination, which can be modeled as complex Gaussian random variables with zero mean and variance (sigma ^{2}_{d}).

With the decomposition, the complex MP coefficients are obtained, and modeled as the complex Gaussian distribution which is a suitable one according to the results of GOF test.

These are as complex as they sound.

The degree to which the mechanics of live cells can usefully be modeled as highly complex polymer networks is by no means certain, and this article will discuss recent progress in quantitatively measuring cytoskeletal polymer systems and relating them to the properties of the cell.

We suppose that the duplexer is frequency flat as it is customarily done in the literature [5, 15, 16] and modeled as a complex gain introduced by the coupling at the oscillator.

We assume that {h k } are independent and identically distributed over K users, each modeled as a complex Gaussian random variable with E{|h k (n)|2} = 1, i.e., h k ( n ) ∼ C N ( 0, 1 ).