一种基于信任值的移动二次用户协同频谱感知算法

Xinyu Wang, Min Jia, Qing Guo, Xuemai Gu
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引用次数: 6

摘要

认知无线电能够有效地提高频谱利用率。然而,协同频谱感知给恶意用户提供了干扰其决策过程的机会。当移动二次用户的能量检测结果变得不可靠时,传统的基于信任值的协同频谱感知算法无法区分是可靠用户进入深度衰落区域还是恶意攻击。这就是为什么当次要用户是移动用户时,传统算法的检测性能非常差的主要原因。针对移动二次用户,提出了一种基于信任值的协同频谱感知算法。我们根据不同区域的实际信道情况将整个区域划分为小区,使得用户在任意一个小区的检测结果非常接近,而在不同小区的检测结果却相差很大。我们提出的方法基于恶意用户的信任值,在每个计算单元中独立移除恶意用户。信道条件较好的小区赋予较大的加权系数。然后分析了二次用户平均速度对检测性能的影响。仿真结果表明,当二次用户为移动用户时,本文算法的检测性能远优于传统的静态二次用户基于信任值的协同频谱感知算法,也优于考虑位置信道差异的基于位置可靠性和恶意意图的移动认知无线网络可信协同频谱感知算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A trust-value based cooperative spectrum sensing algorithm for mobile secondary users
Cognitive radio is able to effectively increase spectral utilization. However, cooperative spectrum sensing gives malicious users chances to interfere with its decision processes. If a mobile secondary user's energy detection results become unreliable, conventional trust-value based cooperative spectrum sensing algorithms, which are used to resist malicious attacks, cannot distinguish whether it's caused by a reliable user moving into a deep-fading area or it attacking maliciously. This is the main reason why the detection performances of conventional algorithms are terribly bad when secondary users are mobile. This paper proposes a trust-value based cooperative spectrum sensing algorithm aiming at mobile secondary users. We divide the whole region into cells according to different areas' actual channel conditions so that the detected results of users in any one of cells are very close to each other but those in different cells are quite different. Our proposed approach removes malicious users independently in each cell based upon their trust values. And larger weighting coefficients are given to cells with better channel conditions. Then this paper analyzes the effects of the average velocity of secondary users on the detection performance. Simulation results show that when secondary users are mobile, the detection performance of our algorithm is much better than that of conventional trust-value based cooperative spectrum sensing algorithms proposed for static secondary users and is better than that of a trusted collaborative spectrum sensing for mobile cognitive radio networks based upon location reliability and malicious intention which also takes location channel differences into considerations.
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