Improved Cyclostationary Spectrum Sensing Scheme for Primary Users Randomly Arriving
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摘要: 在认知无线电(CR)网络中，针对检测频段突然被主用户(PU)占用导致次用户频谱检测性能较差的情况。该文提出一种基于反馈叠加原理的改进循环平稳特征检测算法，该算法通过将检测周期后半部分采样点的瞬时采样值累加到检测周期前半部分采样点的瞬时采样值上，在不延长检测时间的基础上，提高了整个检测周期的判决统计值，从而提高了系统检测性能。并且从理论上详细分析了该算法的检测概率，虚警概率与吞吐量。仿真结果表明，该算法的检测性能优于传统循环平稳特征检测算法和传统能量检测算法，并且保证了不错的用户数据吞吐量。Abstract: In the Cognitive Radio (CR) networks, the detection performance of Primary Users (PU) randomly arriving during the sensing period is poor. So, an improved spectrum sensing method exploiting the cyclostationary feature is proposed, which adds the second half sampling values of sampling signal to the first half. The method improves the detection performance by enhancing the test statistic even though the sensing time is not added. Then, detection probability, false probability and throughput are analysed theoretically. Simulation results show that the proposed method performs better on detection performance and throughput than the conventional spectrum detection and the conventional cyclostationary spectrum sensing.
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