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Ant Colony Optimization-based Resource Allocation and Resource Sharing Scheme for V2V Communication

机译:基于蚁群优化的V2V通信资源分配与共享方案

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The innovative architecture of Device-to-Device (D2D) underlying LTE/LTE-A networks is brought up to enable efficient discovery and communication between proximate devices. However, enabling D2D communications in a cellular network poses a major challenge that Quality of Service (QoS) requirements of D2D communications need to be guaranteed. Thus, synchronization between devices becomes a necessity and Radio Resource Management (RRM) becomes a key design aspect to enable D2D communication, where resource allocation phase is one of the most critical aspects. The problem of resource allocation in D2D communication system is a combinatorial optimization issue, difficult to obtain optimum solutions in polynomial time. In order to reduce complexity, it can be solved by using linear algorithms or by metaheuristic methods. In this paper an Ant Colony Optimization (ACO) based resource allocation and resource sharing scheme for Vehicle-to-Vehicle (V2V) based D2D communications in LTE-A networks is introduced. The swarm intelligence algorithm ACO, which is a typical algorithm of metaheuristic methods, is adopted to resolve the optimization problem of maximizing the network sum rate while considering the QoS requirements.
机译:提出了基于LTE / LTE-A网络的设备到设备(D2D)的创新架构,以实现有效的发现和邻近设备之间的通信。但是,在蜂窝网络中启用D2D通信提出了一项重大挑战,即必须确保D2D通信的服务质量(QoS)要求。因此,设备之间的同步成为必要,无线电资源管理(RRM)成为实现D2D通信的关键设计方面,其中资源分配阶段是最关键的方面之一。 D2D通信系统中的资源分配问题是组合优化问题,难以在多项式时间内获得最优解。为了降低复杂度,可以使用线性算法或元启发式方法来解决。本文介绍了一种基于蚁群优化(ACO)的资源分配和资源共享方案,用于LTE-A网络中基于车对车(V2V)的D2D通信。采用群体智能算法ACO,一种典型的元启发式算法,解决了在考虑QoS要求的同时最大化网络总速率的优化问题。

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