基于多分辨率信号分解的低轨通信卫星频谱感知

The LEO Satellite Spectrum Sensing Based on the Multi-resolution Signal Decomposition

选择合适的频率分辨率进行能量检测是低轨卫星通信频谱感知的关键技术,分辨率过大会造成漏检,分辨率过小会增加计算量并且造成虚警。另外由于反向链路的感知数据需要发送到地面站进行综合判决,数据量越小越利于传输。为了提高检测精度和降低数据传输量,该文提出基于多分辨率信号分解技术的低轨通信卫星频谱感知,仿真结果表明:在反向感知数据传输中,利用多分辨率信号分解技术在大幅减少频谱感知数据量时,仍能良好保持谱密度函数的特征;在频谱空穴检测中,多分辨率信号分解技术与固定分辨率检测技术相比,大幅提高了空穴定位的收敛速度,同时减少了空穴数量的统计误差。

In the LEO satellite spectrum sensing,choosing a proper frequency resolution for detecting the energy is very crucial. A too high resolution fails to detect spectrum holes which probably exist,while a too low one adds the computation and misjudges the jitter in frequency-domain as holes. Moreover,because backward-link sensing data need to be transferred to ground stations to do synthesis and detection,it is obvious that the smaller the quantity of data is,the easier for it to be transmitted. In order to improve the detecting accuracy and to reduce transmitting information,this paper proposes a LEO satellite spectrum sensing based on the multi-resolution signal decomposition. The simulation of this technology concludes that in backward sensing data transmission,multi-resolution signal decomposition can keep well shape of power spectral density function while largely decreasing spectrum sensing data. Besides,in the process of spectrum hole detecting,compared to fixed-resolution detecting,this technology can raise greatly the convergence rate of spectrum hole location and meantime reduce statistical error of holes.