Impact of the propagation model on the capacity in small‐cell networks: comparison between the UHF/SHF and the millimetre wavebands

• Autor(a) principal: Teixeira, Emanuel
• Data de Publicação: 2021
• Outros Autores: Sousa, Sofia, Velez, Fernando J., Peha, Jon
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.6/11114
• topic: Urban/vehicular; Pedestrian; Urban micro; Mofdified Friis propagation model; Manhattan grid topology; Small-cell networks; Sub-6GHz; Millimetre wavebands; UHF/SHF; Two-slope propagation model; Supported throughput; Signal-to-interference-plus-noise ratio

This work shows how both frequency and the election of path loss model affect estimated spectral efficiency. Six different frequency bands are considered, ranging from 2.6 GHz in the Ultra High Frequency (UHF) band to 73 GHz in the millimetre wave bands (mmWaves), using both single-slope and two-slope path-loss models. We start by comparing four ur ban path loss models for UHF: the urban/vehicular and pedestrian test environment from the ITU-R M. 1255 Report, which includes the two-slope urban micro line-of-sight (LoS) and NLoS, from the ITU-R 2135 Report. Then, we consider mmWaves taking into con26 sideration the modified Friis propagation model, followed by an analysis of the through put for the 2.6, 3.5, 28, 38, 60 and 73 GHz frequency bands. We have found that the signal to-interference-plus-noise ratio, as estimated with the more realistic two-slope model, is lower for devices that are within the break-point of the transmitter, which is a small dis tance in the UHF/SHF band. As a result, spectral efficiency is higher with mmWaves than with UHF/SHF spectrum when cell radius is under 40 meters but not when cells are larger. Consequently, mmWaves spectrum will be more valuable as cells get small. We also find that capacity as estimated with the two-slope model is considerably smaller than one would obtain with the one-slope model when cells are small but there is little difference in the models when cells are larger. Thus, as cells get smaller, the use of one slope models may underestimate the number of cells that must be deployed.