English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Careful network planning has become increasingly critical with the rising deployment, coverage, and congestion of wireless local area networks (WLANs).This paper  investigates and determine the Path-loss exponent value for the ubiquitous wireless local area network at the Federal University Oye-Ekiti for the line of sight and non-line of sight (N-LOS). Aside this, the paper also models the wireless network using artificial neural network (ANN) technology by training some neurons based on data collected from a drive-test. The proposed ANN model performed with accuracy and is offered as a simple, yet strong predictive model for network planning – having both speed and accuracy. Results show, that for the area under study, Oye Campus has a higher   standard deviation of 5.76dBm as against ikole Campus with 1.44dBm, this is because of dense vegetation at Oye Campus. In view of this, the paper provides a predictive site survey for rapid wireless Access point deployment.

Channel Path-Loss Measurement and Modeling in Wireless Data Network (IEEE 802.11n) Using Artificial Neural Network