Methods for Modelling of Overall Telecommunication Systems Stoyan Poryazov, Velin Andonov, and Emiliya Saranova Abstract The aim of the paper is to summerize some of the methods for modeling of overall telecommunication systems developed by the authors at the Institute of Math- ematics and Informatics of the Bulgarian Academy of Sciences and to propose new methods using the apparatus of the Generalized Nets (GNs) theory. On the basis of the discussed methods, two basic tasks about overall telecommunication systems are formulated. Analytical models for solving the Quality of Service (QoS) prediction task and the Network Dimensioning/Redimensioning Task (NDT/NRDT) are pro- posed. A classical model of overall telecommunication system is considered. General teletraffic tasks are formulated on the basis of a proposed conceptual model. Some assumptions for the system are stated which allow for a relatively simple analyti- cal model to be obtained. Analytical expressions for basic teletraffic characteristics of the main tasks about overall telecommunication systems are derived. Graphical representation of the results is included. A comparison with other approaches for network dimensioning is made and is represented graphically Keywords Overall telecommunication system · Conceptual modeling · Quality of service · Overall network dimensioning/redimensioning 1 Introduction Despite the long-standing use of the telecommunication systems in practice, their modelling is still an object of current development. The aim of the paper is to summarize some of the methods for conceptual and analytical modeling of overall S. Poryazov · V. Andonov (B ) · E. Saranova Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Block 8, 1113 Sofia, Bulgaria e-mail: velin_andonov@math.bas.bg S. Poryazov e-mail: stoyan@math.bas.bg E. Saranova e-mail: emiliya@math.bas.bg © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 K. T. Atanassov (ed.), Research in Computer Science in the Bulgarian Academy of Sciences, Studies in Computational Intelligence 934, https://doi.org/10.1007/978-3-030-72284-5_16 325