Abstract
The Internet of Things (IoT) is a promising paradigm to accommodate massive device connections in future-generation mobile communications networks. Due to spectrum scarcity issues, mobile operators will exploit current cellular networks’ existing standards and infrastructures to deploy IoT networks within the licensed cellular spectrum. Sharing and partitioning spectrum are approaches to simultaneously coping with massive IoT and mobile cellular connections (IoT-Cellular). However, the IoT-Cellular capacity is highly limited due to the finite number of licensed spectrum bands and the complicated co-channel interference provoked by proximity of massive IoT devices. It is assumed that the IoT-Cellular network is responsible for reducing its interference with the cellular network. Under such interference regulation to mobile cellular bands, we propose a two-stage suboptimal algorithm that sequentially performs channel assignment and power control, maximizing the channel capacity and devices attended while guaranteeing link channel Quality of Service (QoS). For channel allocation, the Proportional Fair (PF) algorithm was applied. Transmit power allocation is a non-convex problem with an NP-hard nature; therefore, we proposed a heuristic scheme based on a genetic algorithm to solve it. Our proposal is evaluated concerning sharing and partitioning spectrum techniques. Also, the IoT network capacity and the number of attended devices are analyzed under conditions of further densification. Results show that more IoT devices are attended to when interference coordination is efficiently applied and network-capacity degradation is minimized.
This research was funded in part by the National Council of Science and Technology (CONACyT, México) through the Fondo Sectorial de Investigación para la Educación, under Grant number 288670-Y.
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Anzaldo, A., Andrade, Á.G. (2023). Interference-Aware Power Control for Spectrum Sharing Massive-IoT Communications. In: Bravo, J., Ochoa, S., Favela, J. (eds) Proceedings of the International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2022). UCAmI 2022. Lecture Notes in Networks and Systems, vol 594. Springer, Cham. https://doi.org/10.1007/978-3-031-21333-5_46
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DOI: https://doi.org/10.1007/978-3-031-21333-5_46
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