认知无线电网络中次用户平均吞吐量的优化

发布时间：2018-04-26 17:10

本文选题：认知无线电网络(CRN) + 协作频谱感知　；参考：《电子与信息学报》2014年07期

【摘要】：协作频谱感知的认知无线电网络中,已有研究表明增加参与协作频谱感知的次用户数量能够提高感知性能,进而提高信道吞吐量。然而,由于信道容量的限制,不断增加参与协作感知的次用户数量并不会使信道吞吐量无限提高,反而会使次用户平均可获得的吞吐量不断降低。针对上述问题,该文以次用户平均吞吐量为优化目标,证明多信道条件下,对于任意给定的融合参数,次用户的平均吞吐量是感知时间的凸函数,并提出交叉迭代算法进行2维优化。仿真结果表明,当信噪比为-10 dB时,次用户使用交叉迭代算法获得的平均吞吐量较已有算法可提高20%以上。
[Abstract]:In cognitive radio networks with cooperative spectrum sensing, it has been shown that increasing the number of secondary users participating in cooperative spectrum sensing can improve the perception performance and thus improve the channel throughput. However, due to the limitation of channel capacity, increasing the number of secondary users participating in cooperative awareness will not increase the channel throughput infinitely, but decrease the average throughput of secondary users. Aiming at the above problems, this paper takes the average throughput of secondary users as the optimization objective, and proves that the average throughput of secondary users is a convex function of perceptual time for any given fusion parameter under multi-channel conditions. A cross-iteration algorithm is proposed for 2-D optimization. The simulation results show that when the SNR is -10 dB, the average throughput of the sub-user using the cross-iteration algorithm can be increased by more than 20% compared with the existing algorithm.
【作者单位】：信息工程大学信息系统工程学院;65017部队;
【基金】：国家高技术研究发展计划项目(2012AA121606)资助课题
【分类号】：TN925

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