crn中的盲频谱感知算法综述

Doaa J. Zaidawi, S. Sadkhan
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引用次数: 3

摘要

在认知无线电中,频谱被用于那些可以监控频谱的现代应用中,即替代用户(su)可以使用主用户(PU)实际上无法控制的频谱。任何持份者发现获批准的频谱并非一直/在任何地点运作。为了最大限度地利用频谱,在不与PU交互的情况下,允许su在不使用的情况下访问已经分配给PU的频段。为了避免对PU的干扰,SU CR面临着一项艰巨的任务,即在低信噪比(负dB)区域检测PU信号的存在。这是由于在信号到达SU之前可能发生的多径和阴影导致的信号衰减。对于传感,通常使用能量检测器,但它们在这种噪声条件下存在噪声不确定性问题。信噪比墙是一个操作阈值,超过这个阈值,图像识别就不再可能了。这种模糊性是由于随着时间的推移,噪声方差的计算是多么不精确,以及由于不断变化的噪声方差。本文对认知无线电技术(CRNs)领域的研究人员进行了简要概述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Blind Spectrum Sensing Algorithms in CRNs: A Brief Overview
In cognitive radio, the spectrum is being used in those modern applications that can monitor spectrum, i.e., alternative users (SUs), could use the spectrum that the main user (PU) does not actually control. Any stakeholders have found out that the approved spectrum is not in operation all the time/locations. To maximize spectrum usage, SUs are enabled to get access to frequency bands already allocated to PUs while they are not using it, under the condition that the SUs do not interact with the PU. To avoid interference to the PU, the SU CR faces a difficult task, i.e., detecting the existence of the PU signal in low-SNR (negative dB) area. This is due to signal attenuation due to multipath and shadowing that can occur before the signal hits the SU. For sensing, the energy detectors are commonly used, but they suffer from the noise uncertainty issue in such noise conditions. The SNR wall is the operating threshold at which image identification is no longer possible. This ambiguity is due to how imprecise the calculations of noise variance are over time, and due to the changing noise variance. In this article, a short overview is given for researchers in the field of cognitive radio technology (CRNs).
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