减轻认知无线电网络协同频谱感知控制信道开销的非均匀量化数据融合规则

Arpita Chakraborty, J. Banerjee, Abir Chattopadhyay
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引用次数: 25

摘要

在这篇通信中,作者提出了一种非均匀量化数据融合(N-QDF)规则,减轻了认知无线电系统中基于能量检测的协同频谱感知方案的控制信道开销。虽然软硬或量化数据融合(QDF)技术对每个用户的开销很少,但它在检测性能和复杂性之间提供了一种改进的解决方案。同样,高位QDF比低位QDF提供更大的检测概率,因为低位QDF丢失了更多的信息。本文推导了一种非均匀量化数据融合(N-QDF)规则,该规则可以在给定虚警概率和较高位QDF的情况下,以最小的控制信道开销同时提高检测概率。我们进行了广泛的模拟研究,将可变位N-QDF技术的性能与不同的均匀(即3,4,5位QDF技术)进行比较,以验证我们提出的方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Non-Uniform Quantized Data Fusion Rule Alleviating Control Channel Overhead for Cooperative Spectrum Sensing in Cognitive Radio Networks
In this correspondence, the authors propose a nonuniform quantized data fusion (N-QDF) rule alleviating control channel overhead for energy detection based cooperative spectrum sensing scheme in cognitive radio systems. Though soften hard or quantized data fusion (QDF) technique carries few-bit overhead from each user but it prescribes an improved solution between detection performance and complexity. Again higher-bit QDF provides greater detection probability than lower-bit QDF, due to the loss of more information in lower-bit QDF. In this paper, we derive a non-uniform quantized data fusion (N-QDF) rule that simultaneously enhances the detection probability for a given false alarm probability & higher bit QDF with minimum control channel overhead. We have conducted an extensive simulation study where the performance of variable-bit N-QDF technique is compared with different uniform i.e. 3, 4, 5 bit QDF techniques with respect to different parameters to validate our proposed scheme.
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