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Radio frequency anti-jamming capability improvement for cognitive radio networks: An evolutionary game theoretical approach

机译:认知无线电网络的射频抗干扰能力改进:一种进化博弈论方法

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A cognitive radio is a smart radio that can be programmed and adjusted dynamically on the fly to suit the contextual environmental needs. Many anti-jamming schemes available to protect the Cognitive Radio Networks from jamming attack uses frequency hopping techniques which are deterministic in nature. The deterministic frequency hopping technique is vulnerable to attack at some stage in the real-world scenario. The proposed anti-jamming system for cognitive radio network with adaptive frequency hopping technique efficiently thwarts the RF jamming attack. In the presences of a reactive jammer, two techniques are used to achieve the adaptive frequency hopping: (i) when channel availability reduces below 75 % the Hidden Markov Model (HMM) based algorithm is used, (ii) when the system is in critical state (i.e. channel availability reduces further below 25 %) the interaction between Cognitive radio node and the jammer is modelled using Evolutionary Game Theory (EGT). The results obtained from both models are improved further to find most suitable channel. The simulation results show that the anti-jamming system significantly decreases the probability of bit error to about 48% in the presences of reactive jammer.
机译:认知无线电是一种智能无线电,可以动态地对其进行编程和调整,以适应背景环境的需求。许多可用于保护认知无线电网络免受干扰攻击的抗干扰方案都使用了本质上是确定性的跳频技术。确定性跳频技术在实际情况下的某个阶段很容易受到攻击。所提出的具有自适应跳频技术的认知无线电网络抗干扰系统有效地阻止了RF干扰攻击。在存在电抗干扰器的情况下,可使用两种技术来实现自适应跳频:(i)当信道可用性降低到75%以下时,将使用基于隐马尔可夫模型(HMM)的算法;(ii)当系统处于工作状态时。临界状态(即,信道可用性进一步降低到25%以下),使用进化博弈论(EGT)对认知无线电节点与干扰器之间的交互进行建模。从两个模型获得的结果都得到了进一步改进,以找到最合适的渠道。仿真结果表明,在存在有源干扰器的情况下,抗干扰系统将误码率显着降低到48%。

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