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Capacity Aware Resource Allocation in Millimeter Wave Micro Urban Communication Network

机译:毫米波微型城市通信网络中的容量感知资源分配

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In this changing world, with the advent of technology, users are increasing massively, so are the demands. To cater such demands, there is a need of extensively high bandwidth. Moreover, the current technology of LTE is making is difficult for users to explore the modern technologies like Big Data, IoT fully. Thus, there is a need to move from LTE to 5G. The upcoming 5G emphasizes mainly on providing the following Six requirements i.e, higher capacity, extensively higher data rates, lower End-to-End latency, enormous device-to-device connectivity, less cost and consistent resourcing of Quality of Experience. To address that, 5G implements millimeter Wave which is unused and unlicensed spectrum between 30–300 GHz. In addition to this, the resources are allocated to the system in such a way that each cell is able to use the resources uniformly. In this paper, a hybrid heterogeneous system model is constructed, which has the potential to be working in multi-tier system. In such multi-tier system, one tier is proposed which is comprising of geographic region lying in the Macro base station range which communicates with the small cell base stations using RF communication and the other tier consisting of the region which uses millimeter Wave to communicate within the base stations and UE. A new optimal resource allocation algorithm has been proposed for our multi-tier heterogeneous network which will work upon and analyze the scenario of micro urban and accordingly find out the best possible cell arrangement.
机译:在这个瞬息万变的世界中,随着技术的出现,用户正在大量增加,需求也在不断增加。为了满足这样的需求,需要非常高的带宽。而且,LTE的当前技术正在使用户难以充分探索大数据,物联网等现代技术。因此,需要从LTE过渡到5G。即将到来的5G主要强调提供以下六个要求,即更高的容量,更高的数据速率,更低的端到端延迟,巨大的设备到设备连接性,更低的成本以及一致的体验质量资源。为了解决这个问题,5G实施了毫米波,它是30-300 GHz之间的未使用和未经许可的频谱。除此之外,将资源分配给系统,以使每个小区都能够统一使用资源。本文构建了一个混合异构系统模型,它有可能在多层系统中工作。在这样的多层系统中,提出了一层,该层包括位于宏基站范围内的地理区域,该地理区域使用RF通信与小型小区基站进行通信,而另一层包括由使用毫米波进行通信的区域组成的区域。基站和UE。针对我们的多层异构网络,提出了一种新的最优资源分配算法,该算法将对微型城市的场景进行分析,从而找到最佳的小区配置。

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