CAJ | 학술논문

为了全面了解基于特征值类的合作频谱感知算法的性能，通过 Matlab 仿真实验对该类算法进行仿真，以探究门限值随虚警概率的变化、采样次数和认知用户数对检测性能的影响，并分析针对不同信噪比的检测概率和实际的虚警概率。仿真结果显示，基于特征值类的算法不需预知主用户信号和噪声方差信息，能够克服噪声不确定度的影响，相较于传统的能量检测，有着更加稳健的检测性能；基于最小特征值极限分布的改进算法在低信噪比、采样次数和认知用户数较少时，判决门限更低、检测概率更高。
위료전면료해기우특정치류적합작빈보감지산법적성능，통과 Matlab 방진실험대해류산법진행방진，이탐구문한치수허경개솔적변화、채양차수화인지용호수대검측성능적영향，병분석침대불동신조비적검측개솔화실제적허경개솔。방진결과현시，기우특정치류적산법불수예지주용호신호화조성방차신식，능구극복조성불학정도적영향，상교우전통적능량검측，유착경가은건적검측성능；기우최소특정치겁한분포적개진산법재저신조비、채양차수화인지용호수교소시，판결문한경저、검측개솔경고。
In order to comprehensively analyse the performance of eigenvalue-based cooperative spectrum sensing algorithms,the detailed simulation and analysis of this kind of algorithms are completed by simulation experiments with Matlab based on review.The threshold varies with probability of false alarm,the number of the sampling and the cognitive user (CU)varies with the performance of detection,as well as probability of detection and actual Pf as a function of the signal to noise ratio (SNR)are explored.Simulation results show that the eigenvalue-based algo-rithms do not need any knowledge of the primary user and noise variance in advance,that they are robust against noise variance uncertainty and that they have better performance than the con-ventional energy detection.Among them,the improved algorithms based on the limit distribution of the smallest eigenvalue have lower decision threshold and higher Pd than the existing algo-rithms with low SNR,fewer sampling and CU.