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Multiobjective optimization of fractional frequency reuse for irregular OFDMA macrocellular deployments

机译:不规则OFDMA宏蜂窝部署的分数频率复用的多目标优化

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Interference mitigation has been identified as a key challenge for emerging cellular technologies based on Orthogonal Frequency Division Multiple Access, such as Long Term Evolution. In this context, static intercell interference coordination including Fractional Frequency Reuse (FFR) have been adopted by mobile operators as a good alternative to improve the quality of service at cell edges. Nevertheless, recent results made evident the need for additional research efforts as default FFR configurations only offer tradeoffs in which spectral efficiency is severely penalized. Moreover, the performance of such baseline designs has been showed to be poor in realistic cellular deployments featuring irregular cell patterns. This paper solves this problematic by introducing a novel multiobjective optimization framework based on evolutionary algorithms that jointly takes into account system capacity, cell edge performance, and energy consumption. With respect to important reference schemes, the proposed algorithm succeeds in finding FFR configurations achieving gains between 10 and 40 % in terms of system capacity while simultaneously improving cell edge performance up to 70 %.
机译:对于基于正交频分多址的新兴蜂窝技术(例如长期演进),缓解干扰已被确定为一项关键挑战。在这种情况下,包括小数频率重用(FFR)在内的静态小区间干扰协调已被移动运营商采用,作为提高小区边缘服务质量的良好选择。尽管如此,最近的结果表明,需要进行额外的研究工作,因为默认FFR配置仅在权衡频谱效率的情况下提供了折中方案。而且,在以不规则的细胞模式为特征的实际细胞部署中,已经表明这种基线设计的性能很差。本文通过引入基于进化算法的新颖多目标优化框架解决了这一问题,该框架综合考虑了系统容量,小区边缘性能和能耗。关于重要的参考方案,所提出的算法成功地找到了FFR配置,在系统容量方面实现了10%至40%的增益,同时将蜂窝边缘性能提高了70%。

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