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Dynamic data-driven resource allocation for NB-IoT performance in mobile devices
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DOI：10.1007/s41060-023-00504-7.png)
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Integrating Data-driven Mobile Computing Systems, the narrowband Internet of Things (NB-IoT) emerges as a pivotal communication technology facilitating the realization of a seamlessly interconnected ecosystem. While striving to broaden communication coverage and bolster overall reliability, NB-IoT entails trade-offs in performance benchmarks, notably latency, which can pose challenges in dynamically accommodating mobile IoT devices. In light of these intricacies, this paper introduces a dedicated wireless resource allocation strategy tailored to NB-IoT, specifically focusing on its applicability to mobile devices. Central to this innovative approach is utilizing Kalman filtering to predict the mobile positions of IoT devices. Additionally, the study formulates mathematical models to estimate communication reliability, supplemented by quantitative evaluations encompassing pivotal performance metrics such as block error rate, latency, and energy consumption. The paper further introduces an optimization model and associated radio resource allocation methodologies. Extensive simulation experiments are conducted employing real-world datasets to substantiate the scheme's efficacy. The resultant experimental findings affirm the scheme's ability to effectively ensure a robust connection between mobile IoT devices and base stations and curtail latency concerns.
Keyword:
Block error rate
Dynamic resource allocation
Path loss
NB-IOT
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2.8
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1.1K
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