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We illustrate the application and advantages of the proposed approximation.
We have carried out extensive computer simulations to assess the validity of the proposed approximation tools.
In addition, the numerical results of our experiments confirm the accuracy of the proposed approximation model.
The proposed approximation is based on the extreme value theory of multivariable functions [24].
According to these results, we see that the proposed approximation follows simulated values well.
In this section, we overview the proposed approximation algorithm for the MCDS problem.
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Because its low-complexity and good performance properties, the proposed approximations are suitable for hardware implementation in dedicated architectures.
The proposed approximations are based on certain physical assumptions which simplify the underlying characteristic equation to be solved.
Numerical results demonstrate the superiority of the proposed approximations over the existing formulations, and also good accuracy for the estimation algorithm.
Numerical results are provided to assess the goodness of the proposed approximations, and to highlight their interest in real life applications.
As can be seen from these figures, the LN approximation matches quite well with the simulation results, though the proposed approximations work slightly better with lower fading variance (m = 16).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com