One of the distinctive features of today’s mobile networks is the densification of the access nodes and their heterogeneity, which lead to complex, multi-tier, multi-radio access systems. Unlike previous work, which has focussed on optimal techniques for user assignment and technology selection schemes, in this paper we present a flexible analytical model for the performance evaluation and the efficient design of the above complex systems. Leveraging a Markovian agent formalism, the model captures sev- eral essential elements, including the spatial and temporal dynamics of the user traffic demand and the availability of radio resources. Importantly, the model exhibits low complexity and an excellent match with simulation results; furthermore, it is general enough to accommodate various network architecture and radio technologies. Through an innovative mean-field solution, we derive a number of relevant performance metrics and show the ability of our framework to represent the system behavior in large-scale, real-world scenarios, with time-varying user traffic.

Modelling User Radio Access in Dense Heterogeneous Networks   / Gribaudo, Marco; Manini, Daniele; Chiasserini, Carla Fabiana. - In: PERFORMANCE EVALUATION. - ISSN 0166-5316. - STAMPA. - 146:(2021). [10.1016/j.peva.2020.102167]

Modelling User Radio Access in Dense Heterogeneous Networks  

Carla Fabiana Chiasserini
2021

Abstract

One of the distinctive features of today’s mobile networks is the densification of the access nodes and their heterogeneity, which lead to complex, multi-tier, multi-radio access systems. Unlike previous work, which has focussed on optimal techniques for user assignment and technology selection schemes, in this paper we present a flexible analytical model for the performance evaluation and the efficient design of the above complex systems. Leveraging a Markovian agent formalism, the model captures sev- eral essential elements, including the spatial and temporal dynamics of the user traffic demand and the availability of radio resources. Importantly, the model exhibits low complexity and an excellent match with simulation results; furthermore, it is general enough to accommodate various network architecture and radio technologies. Through an innovative mean-field solution, we derive a number of relevant performance metrics and show the ability of our framework to represent the system behavior in large-scale, real-world scenarios, with time-varying user traffic.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2852608