信道统计未知的认知无线网络抗干扰通信

Qian Wang, K. Ren, P. Ning
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引用次数: 53

摘要

近年来,针对认知无线网络(crn)提出了许多机会频谱感知和接入协议。为了实现优化的频谱使用,现有的解决方案将频谱感知和访问问题建模为部分观察的马尔可夫决策过程(POMDP),并假设信息状态和/或主用户(pu)的流量统计数据是次要用户(su)先验知道的。虽然理论上是合理的,但由于两个主要问题,这些现有的方法在实践中可能并不有效。首先,他们所做的假设是不实际的,因为在通信开始之前,pu的流量统计数据可能不容易提供给su。其次,更严重的是,现有的方法极易受到恶意干扰攻击。认知攻击者总是可以通过利用与SUs相同的统计信息和随机动态决策过程来阻塞要访问的通道。为了解决上述问题,我们制定了crn中的抗干扰多通道接入问题,并将其解决为非随机多臂强盗(NS-MAB)问题,其中辅助发送方和接收方自适应地选择其臂(即发送和接收信道)进行操作。所提出的协议使它们能够在存在干扰的情况下以高概率跳转到同一组信道。我们分析地证明了学习算法的收敛性,即辅助发送方和接收方的最优策略之间的性能差异不超过O(20k/√ε√Tn ln n)。进行了大量的仿真来验证理论分析,并表明所提出的协议对各种干扰攻击具有很高的弹性。
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Anti-jamming communication in cognitive radio networks with unknown channel statistics
Recently, many opportunistic spectrum sensing and access protocols have been proposed for cognitive radio networks (CRNs). For achieving optimized spectrum usage, existing solutions model the spectrum sensing and access problem as a partially observed Markov decision process (POMDP) and assume that the information states and/or the primary users' (PUs) traffic statistics are known a priori to the secondary users (SUs). While theoretically sound, these existing approaches may not be effective in practice due to two main concerns. First, the assumptions they made are not practical, as before the communication starts, PUs' traffic statistics may not be readily available to the SUs. Secondly and more seriously, existing approaches are extremely vulnerable to malicious jamming attacks. A cognitive attacker can always jam the channels to be accessed by leveraging the same statistic information and stochastic dynamic decision making process that the SUs would follow. To address the above concerns, we formulate the problem of anti-jamming multichannel access in CRNs and solve it as a non-stochastic multi-armed bandit (NS-MAB) problem, where the secondary sender and receiver adaptively choose their arms (i.e., sending and receiving channels) to operate. The proposed protocol enables them to hop to the same set of channels with high probability in the presence of jamming. We analytically show the convergence of the learning algorithms, i.e., the performance difference between the secondary sende and receiver's optimal strategies is no more than O(20k/√ε √Tn ln n). Extensive simulations are conducted to validate the theoretical analysis and show that the proposed protocol is highly resilient to various jamming attacks.
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