Energy Efficient Pico Cell Range Expansion and Density Joint Optimization for Heterogeneous Networks with eICIC.
Energy Efficient Pico Cell Range Expansion and Density Joint Optimization for Heterogeneous Networks with eICIC.
复制标题
使用 eICIC 实现异构网络的节能微微蜂窝范围扩展和密度联合优化
DOI：
10.3390/s18030762
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发表时间：
2018-03-02
期刊：
影响因子：
--
通讯作者：
Fang Y
中科院分区：
文献类型：
--
作者：
Sun Y;Xia W;Zhang S;Wu Y;Wang T;Fang Y
由传统宏小区和覆盖的皮科小区构成的异构网络已经被认为是以更高的频谱效率和能量效率（EE）支持大量数据业务的有前景的范例。为了在现实中部署微微小区，皮科基站（PBS）的密度和微微小区范围扩展（CRE）是影响网络频谱效率以及EE改善的两个重要因素。然而，与范围和密度演进相关联，异构架构内的层间干扰将是具有挑战性的，并且时域增强小区间干扰协调（eICIC）技术变得必要。本文综合考虑了上述因素，以提高网络的效率.更具体地说，我们首先推导出封闭形式的表达式的网络EE作为一个函数的PBS的密度和皮科CRE偏置的基础上随机几何理论，其次是线性搜索算法来优化皮科CRE偏置和PBS密度，分别。此外，为了实现皮科CRE偏差和PBS密度的联合优化，提出了一种启发式算法来实现网络EE最大化。数值仿真结果表明，我们提出的皮科CRE偏置和PBS密度联合优化算法可以显着提高网络的EE，计算复杂度低。
Heterogeneous networks, constituted by conventional macro cells and overlaying pico cells, have been deemed a promising paradigm to support the deluge of data traffic with higher spectral efficiency and Energy Efficiency (EE). In order to deploy pico cells in reality, the density of Pico Base Stations (PBSs) and the pico Cell Range Expansion (CRE) are two important factors for the network spectral efficiency as well as EE improvement. However, associated with the range and density evolution, the inter-tier interference within the heterogeneous architecture will be challenging, and the time domain Enhanced Inter-cell Interference Coordination (eICIC) technique becomes necessary. Aiming to improve the network EE, the above factors are jointly considered in this paper. More specifically, we first derive the closed-form expression of the network EE as a function of the density of PBSs and pico CRE bias based on stochastic geometry theory, followed by a linear search algorithm to optimize the pico CRE bias and PBS density, respectively. Moreover, in order to realize the pico CRE bias and PBS density joint optimization, a heuristic algorithm is proposed to achieve the network EE maximization. Numerical simulations show that our proposed pico CRE bias and PBS density joint optimization algorithm can improve the network EE significantly with low computational complexity.
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