This paper shows the procedure and application of the Krige Method (or Kriging) for the analysis of the power level radiated by a Base Station (also called Node B), through a group of samples of this power level, meas...This paper shows the procedure and application of the Krige Method (or Kriging) for the analysis of the power level radiated by a Base Station (also called Node B), through a group of samples of this power level, measured at different positions and distances. These samples were obtained using an spectrum analyzer, which will allow to have georeferenced measurements, to implement the interpolation process and generate coverage maps, making possible to know the power level distribution and therefore understand the behavior and performance of the Node B.展开更多
To reduce network access latency, network traffic volume and server load, caching capacity has been proposed as a component of evolved Node B(e Node B) in the ratio access network(RAN). These e Node B caches reduce tr...To reduce network access latency, network traffic volume and server load, caching capacity has been proposed as a component of evolved Node B(e Node B) in the ratio access network(RAN). These e Node B caches reduce transport energy consumption but lead to additional energy cost by equipping every e Node B with caching capacity. Existing researches focus on how to minimize total energy consumption, but often ignore the trade-off between energy efficiency and end user quality of experience, which may lead to undesired network performance degradation. In this paper, for the first time, we build an energy model to formulate the problem of minimizing total energy consumption at e Node B caches by taking a trade-off between energy efficiency and end user quality of experience. Through coordinating all the e Node B caches in the same RAN, the proposed model can take a good balance between caching energy and transport energy consumption while also guarantee end user quality of experience. The experimental results demonstrate the effectiveness of the proposed model. Compared with the existing works, our proposal significantly reduces the energy consumption by approximately 17% while keeps superior end user quality of experience performance.展开更多
文摘This paper shows the procedure and application of the Krige Method (or Kriging) for the analysis of the power level radiated by a Base Station (also called Node B), through a group of samples of this power level, measured at different positions and distances. These samples were obtained using an spectrum analyzer, which will allow to have georeferenced measurements, to implement the interpolation process and generate coverage maps, making possible to know the power level distribution and therefore understand the behavior and performance of the Node B.
基金the National Natural Science Foundation of China(No.61502038)the Fundamental Research Funds for the Central Universities of China(No.023600-500110002)
文摘To reduce network access latency, network traffic volume and server load, caching capacity has been proposed as a component of evolved Node B(e Node B) in the ratio access network(RAN). These e Node B caches reduce transport energy consumption but lead to additional energy cost by equipping every e Node B with caching capacity. Existing researches focus on how to minimize total energy consumption, but often ignore the trade-off between energy efficiency and end user quality of experience, which may lead to undesired network performance degradation. In this paper, for the first time, we build an energy model to formulate the problem of minimizing total energy consumption at e Node B caches by taking a trade-off between energy efficiency and end user quality of experience. Through coordinating all the e Node B caches in the same RAN, the proposed model can take a good balance between caching energy and transport energy consumption while also guarantee end user quality of experience. The experimental results demonstrate the effectiveness of the proposed model. Compared with the existing works, our proposal significantly reduces the energy consumption by approximately 17% while keeps superior end user quality of experience performance.
