Optimal processing of low power signal in the system of Internet of Things

A. Parshin, Y. Parshin
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Abstract

Among different technologies under investigation for Internet of Things (IoT) one of the most promising is Nar-rowband IoT (NB-IoT). Key feature of this technology is ultra narrow band of signal spectrum. This leads to high influence of low frequency interferences, e.g. flicker noise. This interference has 1/f power spectrum, which allows to use fractal model to describe properties of this random process. The article deals with statistical methods for development of fractal models, e.g. the fractal Brownian motion model with fractional dimension or Hurst exponent. An optimal algorithm for detecting signals on the background of sum of fractal flicker noise and thermal noise is developed and its efficiency is investigated in temporal and spectral field as well. It is proved, that increasing of signal duration leads to spectrum transfer to low frequency area with high intensity of flicker noise spectrum. It leads to decreasing noise resistance.
物联网系统中低功耗信号的优化处理
在物联网(IoT)正在研究的不同技术中,最有前途的技术之一是窄带物联网(NB-IoT)。该技术的关键特点是信号频谱的超窄带。这导致低频干扰的高影响,例如闪烁噪声。该干扰具有1/f功率谱,允许使用分形模型来描述该随机过程的性质。本文讨论了分形模型的统计方法,例如分数维分形布朗运动模型和赫斯特指数分形布朗运动模型。提出了一种分形闪烁噪声和热噪声叠加背景下信号检测的优化算法,并从时间场和光谱场研究了该算法的效率。实验证明,信号持续时间的增加会导致频谱向闪烁噪声频谱强度高的低频区域转移。这导致了噪声阻力的降低。
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