In 5G networks context, both multicast transmissions and dense heterogeneous networks (DenseNet) will be beneficial for improving resource utilization, and increasing coverage and system capacity. Nevertheless, they raise several issues about interference coordination, power consumption, radio resource management and load balancing. In this paper, multicast transmissions are being used in a DenseNet scenario to complement unicast services and support a quality-aware network selection process. In particular, the proposed HUMANS algorithm has been tailored for high-quality video services, which require high datarates and high bandwidth utilization. The analysis carried out shows improved performance when employing HUMANS when varying its different weights assigned to the different parameters in order to achieve its goal.

A Performance Study of a Network Selection Algorithm Employing Multicast Transmissions

P. Scopelliti;A. Tropeano;S. Pizzi;G. Araniti
2019

Abstract

In 5G networks context, both multicast transmissions and dense heterogeneous networks (DenseNet) will be beneficial for improving resource utilization, and increasing coverage and system capacity. Nevertheless, they raise several issues about interference coordination, power consumption, radio resource management and load balancing. In this paper, multicast transmissions are being used in a DenseNet scenario to complement unicast services and support a quality-aware network selection process. In particular, the proposed HUMANS algorithm has been tailored for high-quality video services, which require high datarates and high bandwidth utilization. The analysis carried out shows improved performance when employing HUMANS when varying its different weights assigned to the different parameters in order to achieve its goal.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12318/120025
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