scholarly journals Access Point Placement Recommendation Using Cost-231 Multiwall Propagation

2020 ◽  
Vol 10 (2) ◽  
pp. 103
Author(s):  
Fransiska Sisilia Mukti
Keyword(s):  
Wave Propagation ◽  
Distribution Pattern ◽  
Radio Wave ◽  
Signal Strength ◽  
Access Point ◽  
Propagation Model ◽  
Radio Wave Propagation ◽  
Signal Distribution ◽  
Point Placement

<p class="JGI-AbstractIsi">This study provides an overview of signal distribution pattern using Cost-231 Multi-Wall (MWM) propagation model. The signal distribution pattern is used as a reference in projecting indoor Access Points (AP) placement in Malang Institute of Asia. The MWM approach estimates the actual radio wave propagation value for measurements are made by considering obstacles between APs and user devices. The study recommends 10 optimal points of AP placement for the 1st, 3rd and 4th-floors, and 7 optimal points for the 2nd-floor. Determination of these placement points was based on the estimated signal strength obtained by users, at -50dBM up to - 10dBm, which is the range for good and excellent signal category.</p>

scholarly journals Access Point Placement Recommendation Using Cost-231 Multiwall Propagation

2020 ◽  
Vol 10 (2) ◽  
pp. 103-112
Author(s):  
Fransiska Sisilia Mukti
Keyword(s):  
Wave Propagation ◽  
Distribution Pattern ◽  
Radio Wave ◽  
Signal Strength ◽  
Access Point ◽  
Propagation Model ◽  
Radio Wave Propagation ◽  
Signal Distribution ◽  
Point Placement

This study provides an overview of signal distribution pattern using Cost-231 Multi-Wall (MWM) propagation model. The signal distribution pattern is used as a reference in projecting indoor Access Points (AP) placement in Malang Institute of Asia. The MWM approach estimates the actual radio wave propagation value for measurements are made by considering obstacles between APs and user devices. The study recommends 10 optimal points of AP placement for the 1st, 3rd and 4th-floors, and 7 optimal points for the 2nd-floor. Determination of these placement points was based on the estimated signal strength obtained by users, at -50dBM up to - 10dBm, which is the range for good and excellent signal category.

scholarly journals A Novel Radio Wave Propagation Modeling Method Using System Identification Technique over Wireless Links in East Africa

2018 ◽  
Vol 2018 ◽  
pp. 1-7
Author(s):  
Solomon T. Girma ◽  
Dominic B. O. Konditi ◽  
Ciira Maina
Keyword(s):  
Wave Propagation ◽  
System Identification ◽  
Radio Wave ◽  
Free Space ◽  
Urban Areas ◽  
Radio Channel ◽  
Signal Propagation ◽  
Propagation Model ◽  
Radio Wave Propagation ◽  
Study Region

Transmission of a radio signal through a wireless radio channel is affected by refraction, diffraction and reflection, free space loss, object penetration, and absorption that corrupt the originally transmitted signal before radio wave arrives at a receiver antenna. Even though there are many factors affecting wireless radio channels, there are still a number of radio wave propagation models such as Okumura, Hata, free space model, and COST-231 to predict the received signal level at the receiver antenna. However, researchers in the field of radio wave propagation argue that there is no universally accepted propagation model to guarantee a universal recommendation. Thus, this research is aimed at determining the difference between the measured received signal levels and the received signal level calculated from the free space propagation model. System identification method has been proposed to determine this unknown difference. Measured received signal levels were collected from three randomly selected urban areas in Ethiopia using a computer, Nemo test tool, Actix software, Nokia phone, and GPS. The result from the simulations was validated against the received experimental signal level measurement taken in a different environment. From the simulation results, the mean square error (MSE) was 4.169 dB, which is much smaller than the minimum acceptable MSE value of 6 dB for good signal propagation, and 74.76% fit to the estimation data. The results clearly showed that the proposed radio wave propagation model predicts the received signal levels at 900 MHz and 1800 MHz in the study region.

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