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metadata.dc.type: Artigo de Periódico
Title in Portuguese: A stochastic channel model with dual mobility for 5G massive networks
Author: Pessoa, Alexandre Matos
Guerreiro, Igor Moáco
Silva, Carlos Filipe Moreira e
Maciel, Tarcísio Ferreira
Sousa, Diego Aguiar
Moreira, Darlan Cavalcante
Cavalcanti, Francisco Rodrigo Porto
Issue Date: 2019
Publisher: IEEE
Keywords: Channel modeling
Dual mobility
Spatial consistency
Low complexity
Citation: CAVALCANTI, F. R. P. et al. A stochastic channel model with dual mobility for 5G massive networks. IEEE, [s.l.], v. 7, p. 149971-149987, 2019. DOI: 10.1109/ACCESS.2019.2947407
Abstract: In this paper, a new stochastic channel model (SCM) is proposed for fifth-generation (5G) systems. By means of the sum-of-sinusoids (SoS) method to generate spatially consistent random variables (SCRVs), the proposed model extends the 3rd Generation Partnership Project (3GPP)-SCM by considering three important features for accurate simulations in 5G, i.e., support for dual mobility, spatial correlation at both ends of the link and considerable reductions of the required memory consumption when compared with existing models. A typical problem presented in existing channel models, namely the generation of uncorrelated large scale parameters (LSPs) and small scale parameters (SSPs) for close base stations (BSs), is solved, then allowing for more realistic numerical evaluations in most of the 5G scenarios characterized by a large density of BSs and user equipments (UEs) per unit of area, such as ultra-dense networks (UDNs), indoor environments, device-to-device (D2D) and vehicular-to-vehicular (V2V). The proposed model emerges as the first SCM, and therein lower complexity when compared with ray-tracing (RT)-based models, that comprises all the following features: support for single and dual mobility with spatial consistency, smooth time evolution, dynamic modeling, large antenna array, frequency range up 100 GHz and bandwidth up to 2 GHz. Some of the features are calibrated for single mobility in selected scenarios and have shown a good agreement with the calibration results found in the literature.
ISSN: 2169-3536
Appears in Collections:DETE - Artigos publicados em revista científica

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