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Accessing Spectrum Databases Using Interference Alignment in Vehicular Cognitive Radio Networks

机译:在车辆认知无线电网络中使用干扰对准来访问频谱数据库

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Cognitive radio (CR) vehicular networks are poised to opportunistically use the licensed spectrum for high-bandwidth intervehicular messaging, driver-assist functions, and passenger entertainment services. Recent rulings that mandate the use of spectrum databases have introduced additional challenges in this highly mobile environment, where the CR-enabled vehicles must update their spectrum data frequently and complete the data transfers with roadside base stations (BSs) in very short interaction times. This paper aims to answer two fundamental questions: 1) when to undertake local spectrum sensing, as opposed to accessing spectrum database information at a finite cost overhead; and 2) how to ensure correct packet receptions among the multiple BSs and CR vehicles using fewer slots than the messages that need to be transmitted. The contributions of this paper are twofold: First, we introduce a method of qualifying the correctness of spectrum sensing results using out-of-band 2G spectrum data using experimental results. Second, to the best of our knowledge, this is the first work on applying the concept of interference alignment (IA) in a practical network setting, leading to dramatic reduction in message transmission times. Our approach demonstrates significant reductions in the overhead of direct database queries and improvement in the accuracy of spectrum sensing for mobile vehicles.
机译:认知无线电(CR)车载网络已准备好机会,将许可频谱用于高带宽车载消息传​​递,驾驶员辅助功能和乘客娱乐服务。最近的强制使用频谱数据库的裁决在这种高度移动的环境中带来了其他挑战,在这种环境中,启用CR的车辆必须频繁更新其频谱数据,并在很短的交互时间内完成与路边基站(BS)的数据传输。本文旨在回答两个基本问题:1)何时进行本地频谱感知,而不是以有限的成本开销访问频谱数据库信息; 2)如何使用比需要发送的消息少的时隙来确保多个BS和CR车辆之间正确的分组接收。本文的贡献有两个方面:首先,我们介绍一种使用带外2G频谱数据和实验结果来验证频谱感测结果正确性的方法。第二,据我们所知,这是在实际网络环境中应用干扰对齐(IA)概念的第一项工作,从而大大减少了消息传输时间。我们的方法证明了直接数据库查询开销的显着减少以及移动车辆频谱感测准确性的提高。

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