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Titlebook: Matrix and Analytical Methods for Performance Analysis of Telecommunication Systems; Valeriy Naumov,Yuliya Gaidamaka,Konstantin Samouyl Te

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Block Generator Matriceserator matrices and show how they can be used to obtain solutions to equilibrium equations in matrix product and matrix-geometric form. By applying these methods to .and . service systems, we arrive at matrix generalizations of the Erlang and Wilkinson formulas, namely, used in the Equivalent Random
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Stochastic Lists of Resource Allocationsresources of multiple types are allocated to customers for the total duration of their service times and then released. In such systems, once service is completed, a customer releases the exact amounts of resources that have been allocated to it upon arrival. Thus, for each customer in service we mu
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The Multi-Resource Service System with Service Times Dependent on the Required Amounts of Resourcesrce amounts. We demonstrate that for each such loss system there exists a loss system having the same stationary distribution but whose service times are exponentially distributed and independent of resource requirements.
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Markovian Systems with Random Resource RequirementseLS in which arrivals and departures are governed by a Markov chain and obtain the necessary and sufficient conditions for the stationary distribution to have a product form. Finally, a simplified technique to compute the stationary state distribution using Fourier transform is derived.
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Application Examples and Case StudiesG radio access networks and especially 5G mmWave communications. The main difference of ReLS from classical service systems is that a customer, beside a server, demands a random amount of some limited resources, which is held for the duration of its service time and then released. The resulting mode
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978-3-030-83134-9The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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https://doi.org/10.1007/978-3-030-83132-5Telecommunication Networks; Queueing Systems; Queueing Theory; Markov Chains; Markov Processes; Erlang Lo
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