Wi-Fi Signal Indoor LOS Coverage modeling using PSO-ANFIS

  • Omae Oteri Jomo Kenyatta University of Agriculture and Technology
  • E. N. Ndung'u Jomo Kenyatta University of Agriculture and Technology
  • Kibet Langat Jomo Kenyatta University of Agriculture and Technology

Abstract

Wireless local area networks (WLANS) are becoming very popular in our daily communications applications. Currently in kenya a number of internet service providers like Safaricom, Zuku and others are providing internet access using Wi-Fi. I believe this is replicated world over. This has necessitated studies on these systems to improve on the quality of service (QoS) provided to the users. Different methods have been used in signal modeling. This study is aimed at predicting Wi-Fi signal propagation along a corridor using Particle Swarm Optimization (PSO) trained Adaptive Neural Fuzzy Inference System (ANFIS). The root mean square and standard deviation of the predicted signal were determined. The study was undertaken using a Wi-Fi router as the transmitter and a mobile phone as the receiver in the process of data collection. The measured values were then used in PSO-ANFIS modeling. It was found that the predicted values were close to actual measured values as from the undertaken analysis.
Keywords; Wi-Fi, QoS, WLANS, ANFIS
Published
Jul 13, 2018
How to Cite
OTERI, Omae; NDUNG'U, E. N.; LANGAT, Kibet. Wi-Fi Signal Indoor LOS Coverage modeling using PSO-ANFIS. Proceedings of Sustainable Research and Innovation Conference, [S.l.], p. 269-275, july 2018. ISSN 2079-6226. Available at: <http://sri.jkuat.ac.ke/ojs/index.php/proceedings/article/view/698>. Date accessed: 21 aug. 2019.