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Adaptive resource allocation scheme for cognitive radio vehicular ad-hoc network in the presence of primary user emulation attack

机译:存在主要用户仿真攻击的认知无线电自组织网络的自适应资源分配方案

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摘要

Following the characteristics of the cognitive radio (CR) and the exponential increase of the vehicles, it is envisioned to deploy CR in vehicular ad-hoc network (VANET) in near future. Due to the mobility of the vehicles, it is quite challenging to find the vacant band and to reuse it for data transmission purpose without affecting the primary network. Further, the presence of primary user emulation attack (PUEA) in the VANET makes this task more complicated. Hence, an accurate detection technique and proper power allocation to the vehicular secondary users (VSUs) are the two major factors which need to be addressed for reliable data transmission. Hence this study attempts to evaluate the performance metrics of the CR-VANET considering the spatial correlation among the local decisions of the VSUs in the presence of PUEA. The energy efficiency maximisation with adaptive power allocation to the VSUs is achieved by the authors' proposed scheme based on genetic algorithm under the constraints of interference power to the primary receiver, minimum achievable data rate and maximum transmission power limit. The system performance is investigated in detail through the simulation-based study and analysis.
机译:遵循认知无线电(CR)的特性和车辆的指数级增长,可以预见在不久的将来将CR部署在车辆自组织网络(VANET)中。由于车辆的机动性,找到空闲频带并将其重新用于数据传输目的而不影响主网络是非常具有挑战性的。此外,VANET中主要用户仿真攻击(PUEA)的存在使该任务更加复杂。因此,准确的检测技术和对车辆次要用户(VSU)的正确功率分配是可靠数据传输需要解决的两个主要因素。因此,本研究尝试在存在PUEA的情况下,考虑VSU的本地决策之间的空间相关性,评估CR-VANET的性能指标。作者提出的基于遗传算法的方案,在对主接收机的干扰功率,可达到的最小数据速率和最大传输功率限制的约束下,通过对VSU进行自适应功率分配来实现能效最大化。通过基于仿真的研究和分析,详细研究了系统性能。

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