Spectrum sensing is a key enabling technique for cognitive radio (CR), which provides essential information on the spectrum availability. However, due to severe wireless channel fading and path loss, the primary user (PU) signals received at the CR or secondary user (SU) can be practically too weak for reliable detection. To tackle this issue, we consider in this letter a new intelligent reflecting surface (IRS)-aided spectrum sensing scheme for CR, by exploiting the large aperture and passive beamforming gains of IRS to boost the PU signal strength received at the SU to facilitate its spectrum sensing. Specifically, by dynamically changing the IRS reflection over time according to a given codebook, its reflected signal power varies substantially at the SU, which is utilized for opportunistic signal detection. Furthermore, we propose a weighted energy detection method by combining the received signal power values over different IRS reflections, which significantly improves the detection performance. Simulation results validate the performance gain of the proposed IRS-aided spectrum sensing scheme, as compared to different benchmark schemes.
翻译:光谱感测是认知无线电(CR)的关键赋能技术,它提供有关频谱可用性的基本信息,然而,由于无线频道严重衰减和路径丢失,在CR或二级用户(SU)收到的主要用户(PU)信号实际上太弱,无法可靠地探测。为了解决这一问题,我们在本信中认为,对于CR来说,一种新的智能反映表面(IRS)辅助频谱感测计划是一种新型智能技术,它利用IRS的大型孔径和被动波形增益来提高SU收到的PU信号强度,以便利其频谱感测。具体地说,通过根据特定的代码表动态改变IRS的反射,其在SU的反射信号能量大不相同,用于机会信号探测。此外,我们提出一种加权能源探测方法,将收到的信号功率结合到的不同IRS反射镜的信号值,大大提高了探测性能。模拟结果验证了拟议的IRS辅助频谱测图的性收益,与不同的基准方案相比。