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Energy Efficiency Behavior in Heterogeneous Networks under Various Operating Situations of Cognitive Small Cells

机译:认知小细胞在各种运行情况下异构网络中的能效行为

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Recently, several approaches were followed for the enhancement and better resource utilization in mobile networks; this is to achieve energy efficient consumption for production and delivery of an information bit. Using Cognitive Femto cells (as a member of the small base stations’ family) proves that, it is an efficient solution for achieving this goal[1]. The use of Energy Efficiency term η has become one of the major indices for measuring the performance of these systems. η is the measure of the overall system Capacity (C)?in bps/Hz versus the Consumed Energy (E) in Joules [2]. In consistence with many researches, analytic models and empirical measurements, η will be investigated throughout the course of this work. Cognitive Base Stations (CBS) (as an element of the system model) which performs the traffic offloading operations is proved to enhance η performance. In this work, a combination of both analytic and simulation models are used to construct a practical system model. The obtained model is then used to illustrate the effect of different operational parameters that are involved in the η problem. On the other hand, the current paper tries to focus on the selection criteria that may be used to design the cooperative cognitive networks in order to achieve the best η indices. Both of CBSs radii as well as the inter-separation distances (between CBSs and MBS location) are examined to obtain best η index for different operation scenarios; in addition, both of capacity and energy consumption are taken into consideration based on practical operating measures. This work proposed several nonlinear equations with fixed parameters to be used by field engineers to achieve the results with minimum reduced computation complexity. So, the current work may be of importance for the regulator bodies as well as the cognitive mobile operators.
机译:最近,人们采用了几种方法来增强和更好地利用移动网络中的资源。这是为了实现信息位的生产和传递的节能使用。使用认知毫微微小区(作为小型基站家族的一员)证明,它是实现这一目标的有效解决方案[1]。能源效率项η的使用已成为衡量这些系统性能的主要指标之一。 η是整个系统容量(C)?的单位为bps / Hz,而消耗的能量(E)的单位为焦耳[2]。根据许多研究,分析模型和经验测量,将在整个工作过程中研究η。事实证明,执行流量分流操作的认知基站(CBS)(可以作为系统模型的一部分)可以提高η性能。在这项工作中,分析模型和仿真模型都被结合使用来构建一个实用的系统模型。然后,使用获得的模型来说明η问题中涉及的不同操作参数的影响。另一方面,当前论文试图集中于选择标准,该标准可用于设计合作认知网络以实现最佳η指数。检查CBS半径以及间隔距离(CBS和MBS位置之间),以获得针对不同操作场景的最佳η指数。此外,根据实际操作方法,还要考虑容量和能耗。这项工作提出了几个带有固定参数的非线性方程,供现场工程师用来以最小的计算复杂度来获得结果。因此,当前的工作对于监管机构以及认知移动运营商可能至关重要。

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