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Energy-Efficient Multi-Stream Carrier Aggregation for Heterogeneous Networks in 5G Wireless Systems

机译:5G无线系统中异构网络的高能效多流载波聚合

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Multi-stream carrier aggregation (MSCA) has been recently proposed as a mechanism to increase the amount of bandwidth available to users for heterogeneous networks (HetNets) in 5G wireless systems. Previous studies have focused only on maximizing the network capacity and fairness, without considering the energy efficiency of the MSCA. In this paper, the use of MSCA to minimize the energy consumption in a multi-layer HetNet is studied. The convexity of the energy minimization problem is examined, leading to the need of a quasi-convex relaxation. With this approximation, an algorithm bisection method for energy minimization is designed to solve the energy minimization problem and obtains an optimum cell-association policy. Since the operators are generally interested in a balance between the energy minimization and capacity maximization, such multi-objective optimization is needed, and we studied it in this paper. The two aforementioned conflicting objectives can be jointly analyzed and solved through scalarization, even though the energy minimization has a quasi-convex objective function, and not a convex one. Performance evaluation is provided to identify the achievable energy savings of our proposed algorithm and to characterize the tradeoffs between the energy minimization and capacity maximization in a multi-layer HetNet in 5G systems that support MSCA.
机译:最近已经提出了多流载波聚合(MSCA)作为增加5G无线系统中异构网络(HetNet)用户可用带宽的机制。先前的研究仅关注最大化网络容量和公平性,而没有考虑MSCA的能源效率。本文研究了使用MSCA将多层HetNet中的能耗降至最低。研究了能量最小化问题的凸面性,导致需要准凸弛豫。通过这种近似,设计了一种用于能量最小化的算法二分法,以解决能量最小化问题并获得最佳的小区关联策略。由于运营商通常对能量最小化和容量最大化之间的平衡感兴趣,因此需要这种多目标优化,因此我们在本文中进行了研究。即使能量最小化具有准凸目标函数而不是凸函数,但可以通过标量化共同分析和解决上述两个矛盾的目标。提供性能评估来确定我们提出的算法可实现的节能效果,并表征支持MSCA的5G系统中多层HetNet的能耗最小化和容量最大化之间的权衡。

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