首页> 外文会议>Broadband Access Communication Technologies II; Proceedings of SPIE-The International Society for Optical Engineering; vol.6776 >The Influence of Interference Networks in QoS Parameters in a WLAN 802. 11g: a Bayesian Approach
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The Influence of Interference Networks in QoS Parameters in a WLAN 802. 11g: a Bayesian Approach

机译:WLAN 802. 11g中干扰网络对QoS参数的影响:贝叶斯方法

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In spite of the significant increase of the use of Wireless Local Area Network (WLAN) experienced in the last years, design aspects and capacity planning of the network are still systematically neglected during the network implementation. For instance, to determine the location of the access point (AP), important factors of the environment are not considered in the project. These factors become more important when several Aps are installed, sometimes without a frequency planning, to cover a unique building. Faults such as these can cause interference among the cells generated by each AP. Therefore, the network will not obtain the QoS patterns required for each service. This paper proposes a strategy to determine how much a given network can affect the QoS parameters of another network, by interference. In order to achieve this, a measurement campaign was carried out in two stages: firstly with a single AP and later with two Aps using the same channel. A VoIP application was used in the experiment and a protocol analyzer collected the QoS metrics. In each stage 46 points were measured , that are insufficient for statistically characterize the environment. For expanding this data, an Artificial Neural Network (ANN) was used. After the measurement, an analysis of the results and a set of inferences were made by using Bayesian Networks, whose inputs were the experimental data, I.e., QoS metrics like throughput, delay, jitter, packet loss, PMOS and physical metrics like power and distance.
机译:尽管近年来使用无线局域网(WLAN)的使用显着增加,但是在网络实施期间仍会系统地忽略网络的设计方面和容量规划。例如,在确定接入点(AP)的位置时,项目中未考虑环境的重要因素。当安装了多个Ap(有时不进行频率规划)以覆盖唯一的建筑物时,这些因素变得更加重要。诸如此类的故障可能会在每个AP生成的小区之间造成干扰。因此,网络将无法获得每个服务所需的QoS模式。本文提出了一种策略来确定给定网络可以通过干扰影响多少另一个网络的QoS参数。为了实现这一目标,测量活动分两个阶段进行:首先是使用单个AP,然后是使用同一信道的两个Ap。实验中使用了VoIP应用程序,协议分析器收集了QoS指标。在每个阶段中,共测量了46个点,不足以对环境进行统计表征。为了扩展此数据,使用了人工神经网络(ANN)。测量之后,使用贝叶斯网络对结果进行分析并进行一系列推断,贝叶斯网络的输入是实验数据,即QoS指标(例如吞吐量,延迟,抖动,数据包丢失,PMOS和功率和距离等物理指标) 。

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