Amr A. Fahmy, Asmaa M. Saafan, H. El-Badawy, S. Elramly
{"title":"Energy Efficiency Behavior in Heterogeneous Networks under Various Operating Situations of Cognitive Small Cells","authors":"Amr A. Fahmy, Asmaa M. Saafan, H. El-Badawy, S. Elramly","doi":"10.4236/WET.2015.61002","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":68067,"journal":{"name":"无线工程与技术(英文)","volume":"6 1","pages":"9-23"},"PeriodicalIF":0.0000,"publicationDate":"2015-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4236/WET.2015.61002","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"无线工程与技术(英文)","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.4236/WET.2015.61002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
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.