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Maritime cognitive radio spectrum sensing based on multi-antenna cyclostationary feature detection

机译:基于多天线循环特征检测的海上认知无线电频谱感应

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摘要

With the development of the maritime transportation industry, the number of ships is increasing and the ships are becoming more intelligent. Due to the rapid development of maritime communication, the demand for communication spectrum is increasing. Therefore, the maritime cognitive radio (CR) system is an effective solution. Because of the multipath fading caused by sea surface and atmosphere has a more serious influence on communication signals, which increases the instability of the signal reception, the spectrum sensing technology in maritime cognitive radio is more challenging than the spectrum sensing on land. In order to solve this problem, a cyclostationary detection algorithm for multiple antennas in fading model is proposed. A maximum ratio combining algorithm based on optimal weight correlation value (OWCV-MRC) is proposed for the diversity gain and system performance degradation caused by diversity technology on multipath fading channels. The algorithm uses the correlation values of the attenuation gains on the two different branches as the weighting coefficients of each branch, thus improving the coefficient matrix in the maximum ratio combining (MRC) algorithm. The simulation results show that the proposed algorithm can effectively detect the target signal in the fading channel with ultra-low signal to noise ratio (SNR).
机译:随着海上运输业的发展,船舶数量正在增加,船舶变得越来越聪明。由于海事通信的快速发展,对通信谱的需求正在增加。因此,海上认知无线电(CR)系统是一种有效的解决方案。由于海面和大气引起的多径衰落,大气对通信信号产生了更严重的影响,这增加了信号接收的不稳定性,海上认知无线电的频谱传感技术比陆地上的光谱传感更具挑战性。为了解决这个问题,提出了一种衰落模型中多个天线的循环棘轮检测算法。提出了一种基于最优相关值(OWCV-MRC)的最大比率组合算法,用于多径衰落通道的多样性技术引起的分集增益和系统性能下降。该算法使用两个不同分支上的衰减增益的相关值作为每个分支的加权系数,从而在最大比组合(MRC)算法中提高系数矩阵。仿真结果表明,该算法可以有效地检测衰落通道中的目标信号,以超低信号到噪声比(SNR)。

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