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A fast way to achieve optimum quiet period in cognitive network and its implementation

机译:一种快速的方法来实现认知网络中最佳安静时期及其实现

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IEEE 802.22 wireless regional area networks standard regards base station (BS) as data fusion centre while both BS and customer premises equipments (CPEs) as secondary users (SUs). BS decides the quiet period and sends it to each CPE. Both BS and CPEs would cease transmission in the quiet period so as to detect reliably the primary user's presence. Liang et al. have studied the relation between quiet period and data throughput. It proves that optimal quiet period can be achieved when probability of false alarm is lower than 0.5, while complex computation is necessary if BS needs to find the optimum quiet period. Aiming to reduce the computation effort, we further investigate a look-up table (LUT)-based way to quickly achieve optimal quiet period corresponding to one specific signal-to-noise ratio (SNR) based on maximum ratio combination (MRC). Also, we verify that there exists an effective range of SNR to satisfy the requirement of maximum probability of false alarm, e.g., MRC-based SNR should be greater than -16.3 dB if the maximum probability of false alarm equals 0.1. Finally, to testify the performance in application, a filed programmable gate array-based simulation is performed, the result of which shows that only a delay of 30 ns is needed to output the value of the optimal quiet period after SNR is inputted, indicating its feasibility in the engineering applications.
机译:IEEE 802.22无线区域区域网络标准将基站(BS)视为数据融合中心,而BS和客户房屋设备(CPE)作为辅助用户(SUS)。 BS决定安静时期并将其发送到每个CPE。 BS和CPE都将停止在安静时期的传输,以便可靠地检测主要用户的存在。梁等人。已经研究了安静时期与数据吞吐量之间的关系。它证明,当误报的概率低于0.5时,可以实现最佳安静时期,而如果BS需要找到最佳安静时期,则需要复杂的计算。旨在减少计算工作,我们进一步调查了基于最大比率组合(MRC)的快速实现了与一种特定信噪比(SNR)对应的最佳安静时段的查找表(LUT)。此外,我们验证了有效范围的SNR,以满足误报的最大概率的要求,例如,基于MRC的SNR如果误报的最大概率等于0.1,则应大于-16.3 dB。最后,为了在应用程序中作证性能,执行基于文件的基于栅极阵列阵列的仿真,结果表明只需要延迟30ns以在输入SNR后输出最佳安静时段的值,指示其在工程应用中的可行性。

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