Spectrum Forecasting Model for IoT Services

Manuel Pérez; Daniel Jaramillo; Diana Pinzón; Fabian Herrera

doi:10.1109/APWC.2018.8503788

Spectrum Forecasting Model for IoT Services

Manuel Pérez, Daniel Jaramillo, Diana Pinzón, Fabian Herrera

Departamento de Ingeniería Electrónica

Agencia Nacional Del Espectro (ANE)

Producción: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

2 Citas (Scopus)

Resumen

This paper proposes a novel forecast model for spectrum requirements considering the emerging IoT services for the next 10 years in Colombia. The model includes services in sectors such as health, agriculture, wearable and smart cities, as well as the identification of key attributes that significantly impact the radio spectrum. The proposed model consider short-range communication technologies such as Bluetooth, Wi-Fi, Zigbee and long-range technologies such as cellular networks (2G, 3G and 4G) and LPWAN networks such as Sigfox and LoRa. On the other hand, although the results of the designed model are presented specifically for the Colombian case, it can be adapted in other countries with spectrum planning requirements for IoT services.

Idioma original	Inglés
Título de la publicación alojada	Proceedings of the 2018 8th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2018
Editorial	Institute of Electrical and Electronics Engineers Inc.
Páginas	877-881
Número de páginas	5
ISBN (versión digital)	9781538667651
DOI	https://doi.org/10.1109/APWC.2018.8503788
Estado	Publicada - 23 oct. 2018
Evento	8th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2018 - Cartagena de Indias, Colombia Duración: 10 sep. 2018 → 14 sep. 2018

Serie de la publicación

Nombre	Proceedings of the 2018 8th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2018

Conferencia

Conferencia	8th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2018
País/Territorio	Colombia
Ciudad	Cartagena de Indias
Período	10/09/18 → 14/09/18

ODS de las Naciones Unidas

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10.1109/APWC.2018.8503788

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Pérez, M., Jaramillo, D., Pinzón, D., & Herrera, F. (2018). Spectrum Forecasting Model for IoT Services. En Proceedings of the 2018 8th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2018 (pp. 877-881). Artículo 8503788 (Proceedings of the 2018 8th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/APWC.2018.8503788

Pérez, Manuel ; Jaramillo, Daniel ; Pinzón, Diana et al. / Spectrum Forecasting Model for IoT Services. Proceedings of the 2018 8th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 877-881 (Proceedings of the 2018 8th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2018).

@inproceedings{1ca47fb69edc448792913a4cba56a657,

title = "Spectrum Forecasting Model for IoT Services",

abstract = "This paper proposes a novel forecast model for spectrum requirements considering the emerging IoT services for the next 10 years in Colombia. The model includes services in sectors such as health, agriculture, wearable and smart cities, as well as the identification of key attributes that significantly impact the radio spectrum. The proposed model consider short-range communication technologies such as Bluetooth, Wi-Fi, Zigbee and long-range technologies such as cellular networks (2G, 3G and 4G) and LPWAN networks such as Sigfox and LoRa. On the other hand, although the results of the designed model are presented specifically for the Colombian case, it can be adapted in other countries with spectrum planning requirements for IoT services.",

author = "Manuel P{\'e}rez and Daniel Jaramillo and Diana Pinz{\'o}n and Fabian Herrera",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 8th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2018 ; Conference date: 10-09-2018 Through 14-09-2018",

year = "2018",

month = oct,

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doi = "10.1109/APWC.2018.8503788",

language = "English",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Pérez, M , Jaramillo, D, Pinzón, D & Herrera, F 2018, Spectrum Forecasting Model for IoT Services. En Proceedings of the 2018 8th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2018., 8503788, Proceedings of the 2018 8th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2018, Institute of Electrical and Electronics Engineers Inc., pp. 877-881, 8th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2018, Cartagena de Indias, Colombia, 10/09/18. https://doi.org/10.1109/APWC.2018.8503788

Spectrum Forecasting Model for IoT Services. / Pérez, Manuel ; Jaramillo, Daniel; Pinzón, Diana et al.
Proceedings of the 2018 8th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 877-881 8503788 (Proceedings of the 2018 8th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2018).

Producción: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

TY - GEN

T1 - Spectrum Forecasting Model for IoT Services

AU - Pérez, Manuel

AU - Jaramillo, Daniel

AU - Pinzón, Diana

AU - Herrera, Fabian

PY - 2018/10/23

Y1 - 2018/10/23

N2 - This paper proposes a novel forecast model for spectrum requirements considering the emerging IoT services for the next 10 years in Colombia. The model includes services in sectors such as health, agriculture, wearable and smart cities, as well as the identification of key attributes that significantly impact the radio spectrum. The proposed model consider short-range communication technologies such as Bluetooth, Wi-Fi, Zigbee and long-range technologies such as cellular networks (2G, 3G and 4G) and LPWAN networks such as Sigfox and LoRa. On the other hand, although the results of the designed model are presented specifically for the Colombian case, it can be adapted in other countries with spectrum planning requirements for IoT services.

AB - This paper proposes a novel forecast model for spectrum requirements considering the emerging IoT services for the next 10 years in Colombia. The model includes services in sectors such as health, agriculture, wearable and smart cities, as well as the identification of key attributes that significantly impact the radio spectrum. The proposed model consider short-range communication technologies such as Bluetooth, Wi-Fi, Zigbee and long-range technologies such as cellular networks (2G, 3G and 4G) and LPWAN networks such as Sigfox and LoRa. On the other hand, although the results of the designed model are presented specifically for the Colombian case, it can be adapted in other countries with spectrum planning requirements for IoT services.

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U2 - 10.1109/APWC.2018.8503788

DO - 10.1109/APWC.2018.8503788

M3 - Conference contribution

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T3 - Proceedings of the 2018 8th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2018

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BT - Proceedings of the 2018 8th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2018

PB - Institute of Electrical and Electronics Engineers Inc.

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Y2 - 10 September 2018 through 14 September 2018

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Pérez M , Jaramillo D, Pinzón D, Herrera F. Spectrum Forecasting Model for IoT Services. En Proceedings of the 2018 8th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 877-881. 8503788. (Proceedings of the 2018 8th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2018). doi: 10.1109/APWC.2018.8503788

Spectrum Forecasting Model for IoT Services

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