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Trading off Network Density with Frequency Spectrum for Resource Optimization in 5G Ultra-Dense Networks

机译：权衡频谱的网络密度以优化5G超密集网络中的资源

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摘要

To effectively increase the capacity in 5G wireless networks requires more spectrum and denser network deployments. However, due to the increasing network density, the coordination of network and spectrum management becomes a challenging task both within a single operator’s network and among multiple operators’ networks. In this article, we develop new radio resource management (RRM) algorithms for adapting the frequency spectrum and the density of active access nodes in 5G ultra-dense networks (UDNs) to the traffic load and the user density in different geographical areas of the network. To this end, we formulate a network optimization problem where the allocation of spectrum bandwidth and the density of active access nodes are optimized to minimize a joint cost function, and we exploit Lagrange duality techniques to develop provably optimal network-scheduling algorithms. In particular, we develop density algorithms for two application scenarios. The first scenario solves the resource management problem for an operator of an ultra-dense network with exclusive access to a pool of frequency resources, while the second scenario applies to the management of the network density of collocated UDNs that belong to multiple operators sharing the same frequency spectrum. Simulation results demonstrate how effectively the algorithms can adapt the allocation of the spectrum allocation and the density of active access nodes over space and time.
机译：为了有效地增加5G无线网络的容量，需要更多的频谱和更密集的网络部署。但是，由于网络密度的不断提高，网络和频谱管理的协调成为单个运营商网络内部和多个运营商网络之间的一项艰巨任务。在本文中，我们开发了新的无线电资源管理（RRM）算法，以使5G超密集网络（UDN）中的频谱和活动接入节点的密度适应网络中不同地理区域的流量负载和用户密度。为此，我们提出了一个网络优化问题，其中对频谱带宽的分配和活动接入节点的密度进行了优化，以最大程度地降低了联合成本函数，并且我们利用拉格朗日对偶技术来开发可证明的最佳网络调度算法。特别是，我们针对两种应用场景开发了密度算法。第一种情况解决了超密集网络的运营商具有独占访问频率资源池的资源管理问题，而第二种情况则适用于管理属于多个共享同一频率的运营商的并置UDN的网络密度的管理频谱。仿真结果证明了该算法如何有效地适应频谱分配的分配以及活动接入节点在空间和时间上的密度。

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