Abstract
In order to provide interactive capabilities within the context of Internet of Thing (IoT) applications, wireless communication systems play a key role, owing to inherent mobility, ubiquity and ease of deployment. However, in order to comply with Quality of Service (QoS) and Quality of Experience (QoE) metrics, coverage/capacity analysis must be performed, in order to account for the impact of signal blockage as well as multiple interference sources. This analysis is especially complex in the case of indoor scenarios, such as those derived from Industrial Internet of Things (IIoT). In this work, a fully volumetric approach is employed in order to provide precise wireless channel characterization and hence, system level analysis of indoor scenarios. The proposed methodology will be tested against a real measurement scenario, providing full flexibility and scalability for adoption in a wide range of IIoT capable environments.
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References
Colombo, W., Karnouskos, S., Kaynak, O., Shi, Y., Yin, S.: Industrial cyber physical systems: A backbone of the fourth industrial revolution. IEEE Ind. Electron. Mag. 11(1), 6–16 (2017)
Lu, C., et al.: Real-time wireless sensor-actuator net-works for industrial cyber-physical systems. Proc. IEEE 104(5), 1013–1024 (2016)
Stenumgaard, J., Chilo, J., Ferrer-Coll, J., Angskog, P.: Challenges and conditions for wireless machine-to-machine communications in industrial environments. IEEE Commun. Mag. 51(6), 187–192 (2013)
Candell, R.: Industrial wire-less systems: radio propagation measurements. In: NIST Tech. note 1951, NIST, Gaithersburg, MA, USA, January 2017
Cheffena, M.: Industrial wireless sensor networks: channel modeling and performance evaluation. EURASIP J. Wirel. Commun. Netw. 2012(1), September 2012 https://doi.org/10.1186/1687-1499-2012-297
Cardieri, P.: Modeling interference in wireless Ad Hoc networks. IEEE Commun. Surv. Tuts. 12(4), 551–572 (2010)
Savazzi, S., Rampa, V., Spagnolini, U.: Wireless cloud networks for the factory of things: Connectivity modeling and layout design. IEEE Internet Things J. 1(2), 180–195 (2014)
Garcia, M., Tomas, J., Boronat, F., Lloret, J.: The development of two systems for indoor wireless sensors self-location. Ad Hoc Sens. Wirel. Networks 8(3–4), 235–258 (2009)
Garcia, M., Martinez, C., Tomas, J., Lloret, J.: Wireless sensors self-location in an indoor WLAN. In: International Conference on Sensor Technologies and Applications. SENSORCOMM, Valencia, Spain, 14–20 October 2007
Azpilicueta, L., Rawat, M., Rawat, K., Ghannouchi, F.M., Falcone, F.: A ray launching-neural network approach for radio wave propagation analysis in complex indoor environments. IEEE Trans. Antennas Propag. 62(5), 2777–2786 (2014)
Azpilicueta, L., Falcone, F., Janaswamy, R.: A hybrid ray launching-diffusion equation approach for propagation prediction in complex indoor environments. IEEE Antennas Wirel. Propag. Lett. 16, 214–217 (2017)
Casino, F., Azpilicueta, L., Lopez-Iturri, P., Aguirre, E., Falcone, F., Solanas, A.: Optimized wireless channel characterization in large complex environments by hybrid ray launching-collaborative filtering approach. IEEE Antennas Wirel. Propag. Lett. 16, 780–783 (2017)
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Picallo, I., Iturri, P.L., Celaya-Echarri, M., Azpilicueta, L., Falcone, F. (2021). Integration of Wireless Communication Capabilities to Enable Context Aware Industrial Internet of Thing Environments. In: Peñalver, L., Parra, L. (eds) Industrial IoT Technologies and Applications. Industrial IoT 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 365. Springer, Cham. https://doi.org/10.1007/978-3-030-71061-3_10
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DOI: https://doi.org/10.1007/978-3-030-71061-3_10
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