双层HetNets的吞吐量和回程能源效率分析:一种多目标方法

H. Pervaiz, Zhengyu Song, Leila Musavian, Q. Ni, Xiaohu Ge
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引用次数: 1

摘要

第五代(5G)网络将在异构网络(HetNets)上进行折衷,将宏蜂窝与低功率小蜂窝叠加,通过将信噪比低的用户从宏蜂窝转移到小蜂窝,实现更高的吞吐量。本文提出了一个多目标优化问题(MOP),利用ω-公平效用函数,对两层HetNets下行传输方案中两种不同回程技术的吞吐量和回程能效(BEE)之间的权衡进行了研究。然后,我们利用加权和方法将所提出的MOP转化为单目标优化问题(SOP),以获得具有最小QoS要求和速率公平水平ω的完整Pareto边界解集。变换后的SOP采用拉格朗日对偶分解(LDD)迭代求解,子梯度法给出了近似最优解。仿真结果表明,通过动态调整加权系数α和速率公平水平ω,可以有效地降低与回运技术无关的总面积功耗。我们的数值结果还证明了吞吐量和BEE在不同参数(如权重系数α和速率公平水平ω)下的基本权衡。
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Throughput and backhaul energy efficiency analysis in two-tier HetNets: A multiobjective approach
Fifth Generation (5G) networks will compromise of heterogeneous networks (HetNets) with macrocell overlaid with lower power small cells to achieve higher throughput by offloading users with low signal-to-noise-ratio from macrocell to the small cells. In this paper, we proposed a multi-objective optimization problem (MOP) to jointly investigate the tradeoff between throughput and backhaul energy efficiency (BEE) using ω-fair utility function for two different backhauling technologies in downlink transmission scheme of a two-tier HetNets. We then transform the proposed MOP into a single objective optimization problem (SOP) employing the weighted sum method to obtain the complete Pareto Frontier solution set with minimum QoS requirements and rate fairness level ω. The transformed SOP is solved in an iterative manner using Lagrangian Dual Decomposition (LDD) with a subgradient method providing a near-optimal solution. Simulation results demonstrate the effectiveness of our proposed approach in reducing the total area power consumption irrespective of the backhauling technology by dynamically adjusting weighting coefficient α and rate fairness level ω. Our numerical results also demonstrate the fundamental tradeoff between throughput and BEE for different parameters such as weighting coefficient α and rate fairness level ω.
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