The influence of interference networks in QoS parameters in a WLAN 802.11g: a Bayesian approach

Jasmine P. L. Araújo; Josiane C. Rodrigues; Simone G. C. Fraiha; Hermínio S. Gomes; Jacklyn Reis; Nandamudi L. Vijaykumar; Gervásio P. S. Cavalcante; Carlos R. L. Francês

doi:10.1117/12.734604

10 September 2007 The influence of interference networks in QoS parameters in a WLAN 802.11g: a Bayesian approach

Jasmine P. L. Araújo, Josiane C. Rodrigues, Simone G. C. Fraiha, Hermínio S. Gomes, Jacklyn Reis, Nandamudi L. Vijaykumar, Gervásio P. S. Cavalcante, Carlos R. L. Francês

Author Affiliations +

Proceedings Volume 6776, Broadband Access Communication Technologies II; 677604 (2007) https://doi.org/10.1117/12.734604
Event: Optics East, 2007, Boston, MA, United States

Abstract

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.

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Jasmine P. L. Araújo, Josiane C. Rodrigues, Simone G. C. Fraiha, Hermínio S. Gomes, Jacklyn Reis, Nandamudi L. Vijaykumar, Gervásio P. S. Cavalcante, and Carlos R. L. Francês "The influence of interference networks in QoS parameters in a WLAN 802.11g: a Bayesian approach", Proc. SPIE 6776, Broadband Access Communication Technologies II, 677604 (10 September 2007); https://doi.org/10.1117/12.734604

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