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Nature-Inspired? Optimization in the Era of IoT: Particle Swarm Optimization (PSO) Applied to Indoor-Distributed Antenna Systems (I-DAS)

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The IoT Physical Layer

Abstract

The Internet of Things (IoT) refers to a network type structure (like the Internet) that connects (unique) objects and things. Sensors and devices, integrated into all types of objects, are increasingly connected through wireless networks and, ultimately, the Internet. Already the existing ICT infrastructure accounts for roughly 10% of the global power consumption. By the year 2020, this network will contain 50 billion connected devices and the global IoT/machine-to-machine (M2M) communication market will have a volume of $ 0.5 trillion. Pervasive indoor wireless access has almost become a standard in the first world, but ensuring a thorough and economically sound wireless signal coverage throughout buildings is not a trivial problem. In-building Distributed Antenna Systems (I-DAS) extend wireless access from the base station to distributed antennas through a complex network of coaxial cables and power splitters. For high rise buildings and other multi-unit complexes, the initial cost of I-DAS (cabling and splitters) and the running costs of powering the network are quite significant, motivating the need to optimize the design of I-DAS networks. We propose to utilize Particle Swarm Optimization (PSO) to provide near-optimal network topology. Our PSO model uses Prüfer code representation to efficiently traverse through different spanning tree solutions. Our approach is scalable and robust, capable of producing I-DAS design advice for buildings beyond one hundred floors. We demonstrate that our model is capable of obtaining optimal solutions for small buildings and near-optimal solutions for tall buildings.

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Acknowledgements

This work was supported by UAE ICT Fund, and in part, by Khalifa Semiconductor Research Center and the Semiconductor Research Corporation under the Abu Dhabi SRC Center of Excellence on Energy-Efficient Electronic Systems (\(ACE^{4}S\)), Contract 2013 HJ2440. We acknowledge A. Ouali for his helpful remarks and F. Saffre for early stimulating discussions about the role of naturally inspired computing.

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Authors and Affiliations

  1. Universidad Carlos III de Madrid (UC3M) Dep. de Ingenieria de Sistemas y Automatica - Av. Universidad, 30, 28911, Leganes, Spain

    H. Hildmann

  2. Khalifa University, 127788, Abu Dhabi, UAE

    D. Y. Atia & A. F. Isakovic

  3. EBTIC, Khalifa University, 127788, Abu Dhabi, UAE

    D. Ruta & K. Poon

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  1. H. Hildmann
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Correspondence to A. F. Isakovic .

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  1. Masdar Institute at Khalifa University, Abu Dhabi, United Arab Emirates

    Ibrahim (Abe) M. Elfadel

  2. Wayne State University, Detroit, MI, USA

    Mohammed Ismail

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Hildmann, H., Atia, D.Y., Ruta, D., Poon, K., Isakovic, A.F. (2019). Nature-Inspired? Optimization in the Era of IoT: Particle Swarm Optimization (PSO) Applied to Indoor-Distributed Antenna Systems (I-DAS). In: Elfadel, I., Ismail, M. (eds) The IoT Physical Layer. Springer, Cham. https://doi.org/10.1007/978-3-319-93100-5_11

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  • DOI: https://doi.org/10.1007/978-3-319-93100-5_11

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