实验方法:使用GNU无线电和USRP进行能量和带宽频谱感知

Yanxiao Zhao, Jems Pradhan, Jun Huang, Hui Sun
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引用次数: 2

摘要

频谱感知是成功实现动态频谱接入、提高频谱利用率的重要环节。本文重点研究了利用GNU无线电和通用软件无线电外设(USRP)板进行频谱感知的实验研究。在大多数相关工作中,能量检测方法被广泛用于频谱传感实验,其中接收信号的能量幅值是确定信道状态的唯一参数。具体地说,如果接收到的能量的振幅超过给定的阈值,则检测到通道忙,否则检测到通道空闲。通过观察实验结果,我们发现不需要的信号(可能是干扰信号或噪声信号,也可能是两者兼而有之)的能量幅值通常与需要的信号处于同一水平。如果采用传统的能量检测,会导致误报。同时,在实验室环境中,不需要的信号的带宽通常很窄,在10KHz左右,远远小于常规信号的带宽,例如802.11n中的40MHz和802.11a中的20MHz。受这些观察结果的启发,我们提出了一种新的简单方法,称为能量和带宽频谱传感(EBSS),其中接收信号的能量水平和带宽都被考虑在内。此外,还分析了传感器的虚警检测和脱靶检测性能。进行了大量的实验,结果证明该方法可以显著减少误报和漏检。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Experimental approach: energy-and-bandwidth spectrum sensing using GNU radio and USRP
Spectrum sensing is an essential process to implement dynamic spectrum access successfully and hence improve the spectrum utilization. This paper focuses on an experimental investigation of spectrum sensing using GNU radio and Universal Software Radio Peripheral (USRP) board. In the most related works, the method of energy detection is widely used for experiments on spectrum sensing, in which the energy amplitude of the received signal is the sole parameter to determine a channel's status. Specifically, if the amplitude of received energy exceeds a given threshold, the channel is detected busy, otherwise the channel is sensed idle. By observing experimental results, we find that the energy amplitudes of unwanted signals, which may be either interference or noise or both, are often at the same level as the desired signal. This will lead to a false alarm if the traditional energy detection is employed. At the same time, the bandwidth of unwanted signals are usually narrow and around 10KHz in a lab environment, which is far less than a regular signal's bandwidth, e.g. 40MHz in 802.11n and 20MHz in 802.11a. Inspired by these observations, we propose a new and simple approach termed Energy-and-Bandwidth Spectrum Sensing (EBSS), in which both the energy level and bandwidth of the received signal are taken into account. In addition, the sensing performance including false alarm and miss detection are analyzed. Extensive experiments are conducted and results verify that both false alarm and miss detection can be significantly reduced by the proposed approach.
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