In this article, we present a new queuing network model for the analysis of a portion of a radio access network (RAN) comprising macro cell base stations (BSs) and small cell BSs offering "streaming" and "elastic" services. Streaming services require a certain data rate for a random time. The required data rates depend on the type of service (e.g., audio and video). Elastic services require the transfer of random data volumes, and their data rate adjusts dynamically based on the capacity not utilized by the streaming services. To derive performance measures for the proposed model, we develop a computationally efficient framework that exploits a new product form result for streaming services, relying on a well-known blocking policy, and an approximate product form for elastic services. Insensitivity to the distribution of service requirements holds in the case of negligible end user mobility.We show the high accuracy of our model in predicting the performance of practical system configurations by conducting a thorough comparison between the model's results and those obtained from a detailed discrete-event simulator. Through this analysis, we uncover significant counter-intuitive behaviors that arise from the competition between streaming services with diverse demands, and that are effectively captured and predicted by our modeling approach.Our computationally efficient queuing model is a useful new tool to support design and planning of multi-service RANs whose complex structures result from the coexistence of BSs of different generations in dense areas.

Queuing Network Models of Multiservice RANs

Marin, Andrea
Methodology
;
2024-01-01

Abstract

In this article, we present a new queuing network model for the analysis of a portion of a radio access network (RAN) comprising macro cell base stations (BSs) and small cell BSs offering "streaming" and "elastic" services. Streaming services require a certain data rate for a random time. The required data rates depend on the type of service (e.g., audio and video). Elastic services require the transfer of random data volumes, and their data rate adjusts dynamically based on the capacity not utilized by the streaming services. To derive performance measures for the proposed model, we develop a computationally efficient framework that exploits a new product form result for streaming services, relying on a well-known blocking policy, and an approximate product form for elastic services. Insensitivity to the distribution of service requirements holds in the case of negligible end user mobility.We show the high accuracy of our model in predicting the performance of practical system configurations by conducting a thorough comparison between the model's results and those obtained from a detailed discrete-event simulator. Through this analysis, we uncover significant counter-intuitive behaviors that arise from the competition between streaming services with diverse demands, and that are effectively captured and predicted by our modeling approach.Our computationally efficient queuing model is a useful new tool to support design and planning of multi-service RANs whose complex structures result from the coexistence of BSs of different generations in dense areas.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/5061263
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