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首页> 外文期刊>IEEE Transactions on Signal Processing >Cooperative Spectrum Sensing With Quantization Combining Over Imperfect Feedback Channels
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Cooperative Spectrum Sensing With Quantization Combining Over Imperfect Feedback Channels

机译：不完美反馈通道上的量化量化协作频谱感知

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摘要

A practical fusion rule with quantization combining is proposed for cooperative spectrum sensing over imperfect feedback channels that are inherent in the wireless environment. Local sensor nodes generate decision symbols regarding the existence of a primary user signal by multilevel detection and send them over feedback channels to the fusion center, in which demodulated symbols are combined to draw the cooperative decision. The proposed quantization combining scheme over imperfect feedback channels is analyzed, based on which detection probability and false alarm probability are derived. Operating parameters of the fusion rule with quantization combining are optimally determined under Neyman–Pearson criterion by using a differential evolution algorithm. The proposed fusion rule is compared with other schemes in terms of the detection performance, the amount of system information required for operation, the sensitivity to the channel estimation error, and the computational complexity required for parameter optimization. It is shown that the proposed fusion rule offers the reliable sensing capability even over imperfect feedback channels with requiring small amount of system information and complexity.
机译：提出了一种带有量化组合的实用融合规则，用于无线环境中固有的不完善反馈信道上的协作频谱感知。本地传感器节点通过多级检测生成有关主要用户信号存在的决策符号，并通过反馈通道将其发送到融合中心，在融合中心，解调后的符号将组合在一起以得出合作决策。对不完善的反馈信道上的量化组合方案进行了分析，得出了检测概率和虚警概率。通过使用差分演化算法，在Neyman–Pearson准则下可以最佳地确定具有量化组合的融合规则的操作参数。在检测性能，操作所需的系统信息量，对信道估计误差的敏感性以及参数优化所需的计算复杂度方面，将建议的融合规则与其他方案进行了比较。结果表明，所提出的融合规则即使在反馈路径不完善的情况下，仍具有可靠的感知能力，并且需要少量的系统信息和复杂性。

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