量化报告信道误差下频谱感知的圆形折叠协同功率谱密度分割对消算法性能分析

E. Almeida, L. S. Costa, R. A. Souza, D. Guimarães
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引用次数: 3

摘要

针对认知无线电(CR)应用中集中式协同频谱感知中空闲频段的检测问题,提出了圆形折叠协同功率谱密度分裂对消算法。该算法复杂度低,在非均匀噪声下具有较强的鲁棒性。本文分析了量化信道和误报信道下CF-CPSC的性能。关于CF-CPSC测试统计量,研究了两种方法:i)它完全在融合中心(FC)计算,ii)它在每个CR中部分计算,以节省报告通道资源。在这两种情况下,要由cr报告的信息被统一量化,然后提交给错误。结果表明,CF-CPSC对量化误差和报告误差具有较强的鲁棒性。第二种方法对量化和报告信道误差更敏感,但与第一种方法相比,使用的信道资源更少。通过第二种方法,即使使用纠错代码,也可以实现更小的资源使用,这增加了通过报告通道的数据量。第一种方法使用的资源更大,即使没有纠错码。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance Analysis of the Circular Folding Cooperative Power Spectral Density Split Cancellation Algorithm for Spectrum Sensing Under Errors at the Quantized Report Channel
The circular folding cooperative power spectral density split cancellation (CF-CPSC) algorithm was recently proposed for detecting idle bands in centralized cooperative spectrum sensing for cognitive radio (CR) applications. This algorithm has low complexity and is robust under nonuniform noise. This paper analyzes the performance of the CF-CPSC under quantized and erroneous report channel transmissions. Two approaches has been investigated regarding the CF-CPSC test statistic: i) it is completely computed at the fusion center (FC), and ii) it is partially calculated at each CR for saving report channel resources. In both cases, the information to be reported by the CRs are uniformly quantized and then submitted to errors. Results show that the CF-CPSC is also robust to the quantization and report errors. The second approach is more sensitive to the quantization and report channel errors, but less channel resources are used in comparison with the first approach. The smaller resource usage is achieved by the second approach even with error correcting codes, which increases the amount of data through the report channel. The resource usage achieved by the first approach is larger, even with no error correcting codes.
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