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A distributed solution for cooperative spectrum sensing scheduling in multi band cognitive radio networks

机译:多频带认知无线电网络中协作频谱感知调度的分布式解决方案

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Cognitive Radio (CR) is a promising technology that overcomes the problem of spectrum scarcity and underutilization in an efficient manner. Spectrum sensing is one of the most important functionalities of a Cognitive Radio Network (CRN). Cooperative sensing where multiple sensors cooperatively sense the spectrum proves to be the most efficient way of sensing. However, one of the main challenges in a CRN is how to appropriately schedule the Secondary Users (SU) to sense the potential Primary User (PU) channels cooperatively so that the throughput obtained in the network is optimum. At the same time, in order to protect the quality of service of the PU channels, a minimum sensing performance criteria in terms of probability of detection and false alarm must be satisfied. It can be referred to as Cooperative Sensing Scheduling (CSS) problem. The problem is formulated as a non-linear binary optimization problem that has a high computational complexity. In this paper, the CSS problem is reformulated as an equivalent Integer Linear Programming (ILP) problem which is known to be NP-Complete. A distributed algorithm using coalitional game theoretic approach is proposed that provides near optimal solutions. Numerical results are provided to evaluate the performance of the proposed algorithm and compared with the theoretically optimal results.
机译:认知无线电(CR)是一种有前途的技术,可以有效地克服频谱稀缺和利用率不足的问题。频谱感测是认知无线电网络(CRN)的最重要功能之一。协作感测是多个传感器协同感测频谱的最有效方式。然而,CRN中的主要挑战之一是如何适当地调度次要用户(SU)来协作地感测潜在的主要用户(PU)通道,从而使网络中获得的吞吐量达到最佳。同时,为了保护PU信道的服务质量,必须满足关于检测概率和虚警的最低感测性能标准。可以将其称为协作感知计划(CSS)问题。该问题被公式化为具有高计算复杂度的非线性二进制优化问题。在本文中,CSS问题被重新表述为等效的整数线性规划(ILP)问题,称为NP完全。提出了一种使用联盟博弈论方法的分布式算法,该算法可提供近乎最优的解决方案。提供了数值结果来评估所提出算法的性能,并与理论上的最佳结果进行比较。

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