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Distributed Algorithm for Base Station Assignment in 4G/5G Machine-Type Communication Scenarios with Backhaul Limited Conditions

机译:带回程有限条件的4G / 5G机床类型通信场景中的基站分配分布式算法

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摘要

A progressive paradigm shift from centralized to distributed network architectures has been consolidated since the 4G communication standard, calling for novel decision-making mechanisms with distributed control to operate at the network edge. This situation implies that each base station (BS) must manage resources independently to meet the quality of service (QoS) of existing human-type communication devices (HTC), as well as the emerging machine type communication (MTC) devices from the internet of things (IoT). In this paper, we address the BS assignment problem, whose aim is to determine the most appropriate serving BS to each mobile device. This problem is formulated as an optimization problem for maximizing the system throughput and imposing constraints on the air interface and backhaul resources. The assignment problem is challenging to solve, so we present a simple yet valid reformulation of the original problem while using dual decomposition theory. Subsequently, we propose a distributed price-based BS assignment algorithm that performs at each BS the assignment process, where a novel pricing update scheme is presented. The simulation results show that our proposed solution outperforms traditional maximum signal to interference plus noise ratio (Max-SINR) and minimum path-loss (Min-PL) approaches in terms of system throughput.
机译:自4G通信标准以来,从集中到分布式网络架构的渐进式范式转换已经巩固了,呼吁具有分布式控制的新型决策机制来在网络边缘运行。这种情况意味着每个基站(BS)必须独立地管理资源,以满足现有人类类型通信设备(HTC)的服务质量(QoS),以及来自Internet的新兴机器类型通信(MTC)设备事情(物联网)。在本文中,我们解决了BS分配问题,其目的是确定每个移动设备的最合适的服务BS。此问题的标志为最大化系统吞吐量和对空中接口和回程资源的约束来制定作为优化问题。分配问题是挑战解决,因此我们在使用双分解理论时提出了对原始问题的简单而有效的重新制定。随后,我们提出了一种分布式的基于价格的BS分配算法,该算法在每个BS中执行分配过程,其中提出了一种新颖的定价更新方案。仿真结果表明,我们所提出的解决方案优于传统的最大信号与干扰加噪声比(MAX-SINR)和系统吞吐量方面的最小路径丢失(MIN-PL)方法。

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