QoS-based radio resource management for 5G ultra-dense heterogeneous networks

M. Adedoyin, O. Falowo
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引用次数: 5

Abstract

In the fifth generation wireless networks, the heterogeneous deployment of ultra-dense small cells such as femtocells is seen as a major solution to cope with the exponential traffic growth and to improve coverage especially in indoor environments. However, the unplanned and ultra-dense deployment of femtocells in the coverage area of conventional macrocells introduces new challenges such as cross-tier interference (interference between macrocells and femtocells), co-tier interference (interference between neighbouring femtocells), and inadequate quality of service (QoS) provisioning, which can negatively affect the overall performance of the network. Hence, efficient radio resource management (RRM) algorithms are necessary to address these challenges. Therefore, in this paper, we propose a joint radio resource allocation with adaptive modulation and coding (AMC) scheme. The RRM problem is formulated as an optimization problem, which belongs to the class of mixed integer non-linear programming (MINLP). A reformation-linearization technique (RLT) is introduced to simplify the aforementioned MINLP. Finally, the performance of the proposed algorithm is evaluated and the simulation results show that the proposed algorithm reduces interference and enhances QoS in terms of the overall throughput and fairness when compared with other state-of-the-art algorithms.
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基于qos的5G超密集异构网络无线资源管理
在第五代无线网络中,超密集小型基站(如femtocell)的异构部署被视为应对指数级流量增长和提高覆盖范围(特别是在室内环境中)的主要解决方案。然而,在传统宏基站的覆盖范围内无计划和超密集地部署飞基站带来了新的挑战,如跨层干扰(宏基站和飞基站之间的干扰)、协同层干扰(相邻飞基站之间的干扰)和服务质量(QoS)供应不足,这些都会对网络的整体性能产生负面影响。因此,有效的无线电资源管理(RRM)算法是应对这些挑战的必要条件。因此,本文提出了一种自适应调制编码(AMC)联合无线电资源分配方案。RRM问题被表述为一个优化问题,属于混合整数非线性规划(MINLP)的范畴。引入了一种改造线性化技术(RLT)来简化上述MINLP。最后,对所提算法的性能进行了评估,仿真结果表明,与其他先进算法相比,所提算法在总体吞吐量和公平性方面减少了干扰,提高了QoS。
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