首页> 外文会议>Wireless Communications and Networking Conference Workshops (WCNCW), 2012 IEEE >Use of learning, game theory and optimization as biomimetic approaches for Self-Organization in macro-femtocell coexistence
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Use of learning, game theory and optimization as biomimetic approaches for Self-Organization in macro-femtocell coexistence

机译:在宏毫微微小区共存中使用学习,博弈论和优化作为仿生方法进行自我组织

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In this paper, we present the use of several Biomimetic approaches for Self Organization (SO) in heterogeneous scenarios where macrocell and femtocell networks coexist. Mainly these approaches are categorized in indirect biomimetics and direct biomimetics. Under indirect biomimetics we discuss 1) emerging paradigms in learning theory and 2) game theory for their potential to enable SO solutions in heterogeneous networks. By means of numerical results we demonstrate the pros and cons of these indirect biomimetic approaches for designing SO in macro-femto coexistence scenarios. Furthermore, we demonstrate the use of direct biomimetic approaches for designing SO by exploiting one to one mapping between a natural SO system and our system model for heterogeneous networks based on Outdoor Fixed Relays (OFR). Numerical results show that the proposed analytical solution can enhance wireless backhaul capacity of the OFR based femtocells by adapting the macro base station (BS) antenna tilts in a distributed and self organizing manner.
机译:在本文中,我们介绍了在宏小区和毫微微小区网络共存的异构场景中,几种仿生方法用于自组织(SO)。这些方法主要分为间接仿生和直接仿生。在间接仿生学下,我们讨论1)学习理论中的新兴范式和2)博弈论中它们在异构网络中实现SO解决方案的潜力。通过数值结果,我们证明了这些间接仿生方法在宏观毫微微并存场景中设计SO的利弊。此外,我们通过利用自然SO系统与我们基于室外固定中继(OFR)的异构网络系统模型之间的一对一映射,演示了直接仿生方法在设计SO中的使用。数值结果表明,所提出的分析解决方案可以通过以分布式和自组织的方式适应宏基站(BS)的天线倾斜度,来增强基于OFR的毫微微小区的无线回程容量。

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