Hybrid-based optimization of wireless channel characterization for health services in medical complex environments

Fran Casino, L. Azpilicueta, P. López-Iturri, E. Aguirre, F. Falcone, A. Solanas
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引用次数: 9

Abstract

Nowadays, plenty of simulation techniques based on deterministic methods like Ray Tracing and Ray Launching, combining Geometric Optics and Uniform Theory of Diffraction, are used to predict waves' behaviour within a defined environment and to make better decisions on the deployment of antennas for particular purposes. However, simulations' quality largely depends on the number of rays, providing sufficient angular resolution in the ray launching process. The computational cost of simulations in high definition (HD) prevents their use in complex environments and their low definition (LD) counterparts are used. In this article we propose a technique based on collaborative filtering (CF) to lessen the low quality problems of LD simulations. Such technique outperforms previous works in this field in terms of accuracy, precision and computational cost. Moreover, we show that our approach obtains results very similar to those of HD in much less time. Therefore, using combined deterministic-CF techniques allows the estimation of radio-planning tasks in large, complex medical scenarios with a potentially large amount of transceivers.
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基于混合的医疗复杂环境中健康服务无线信道特性优化
如今,许多基于确定性方法的模拟技术,如射线追踪和射线发射,结合几何光学和均匀衍射理论,被用来预测波在特定环境中的行为,并为特定目的做出更好的天线部署决策。然而,模拟的质量很大程度上取决于光线的数量,在光线发射过程中提供足够的角分辨率。高清晰度(HD)模拟的计算成本阻碍了它们在复杂环境中的应用,而低清晰度(LD)模拟则被使用。在本文中,我们提出了一种基于协同滤波(CF)的技术来减少LD仿真的低质量问题。该技术在精度、精密度和计算成本方面都优于该领域的前人研究成果。此外,我们表明,我们的方法在更短的时间内获得了与HD非常相似的结果。因此,使用组合确定性- cf技术可以在具有潜在大量收发器的大型复杂医疗场景中估计无线电规划任务。
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