Pathloss Measurements and Prediction using Statistical Models

Nadir, Zia; Bait-Suwailam, Mohammad; Idrees, Mohd.

doi:10.1051/matecconf/20165405006

Cited by 11 publications

(11 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The highest level of water steam in the air is based on the changeable temperature of the air. The temperature point implies that the air should cool down so that the water steam reduces into either ice or water (RH = 100%) [7]. Steam from boiling water changes from a gassy state into a solid (deposition, T < 0 • C) state or into a liquid (intensification) state.…”

Section: The Effects Of the New Parameters On The Tymmentioning

confidence: 99%

“…Intensification/deposition begins when the temperature precipitation or the humidity reaches a saturation point of (RH = 100%). The steam from the water is either called clouds (fog) or dew (frost when T < 0 • C), but this depends on the weather condition [7,8].…”

Section: The Effects Of the New Parameters On The Tymmentioning

confidence: 99%

“…However, there is a clear relationship between the signal strength and the temperature. In general, when the temperature increases, the Received Signal Strength Indicator (RSSI) drops [7]. Naturally, the relative humidity the relative humidity increases and drops based on RSSI, which is dependent on a positive relationship with the trend of Absolute Humidity (AH), indicating a negative correlation [8].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

New Empirical Path Loss Model for 28 GHz and 38 GHz Millimeter Wave in Indoor Urban under Various Conditions

et al. 2018

View full text Add to dashboard Cite

Due to rapid development in mobile communication technology in recent years, the demand for high quality and high capacity networks with thorough coverage has become a major necessity. Several models have been developed for predicting wireless signal coverage in urban areas, but these models suffer from inadequately calculating certain conditions, such as weather and building materials, especially window size. In this paper, we propose a new path loss prediction model based on the measurement of new indicators, such as window size, temperature, and humidity conditions, after which an extensive statistical analysis using a linear regression technique was implemented in order to validate the new indicators. As the new indicators were incorporated into the Okumura model to derive a new path loss model, the results showed that the proposed model provides an accurate prediction of the received signal strength in a given propagation environment. Our model enhanced the prediction of path loss by 10% when compared to the Okumura and by 15% when compared to the COST-Hata.

show abstract

Section: The Effects Of the New Parameters On The Tymmentioning

confidence: 99%

Section: The Effects Of the New Parameters On The Tymmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

New Empirical Path Loss Model for 28 GHz and 38 GHz Millimeter Wave in Indoor Urban under Various Conditions

et al. 2018

View full text Add to dashboard Cite

show abstract

“…Among wireless communication architecture, wireless link propagation is the most concerning process to have a success sharing purposes [5] [6]. The environment of radio applications is changing according to environmental factors [7]. Possible resources to the link consideration are based on a better understanding of the environmental factors affecting the link performance of the reliable transmission medium of the radio channel and it is important [8].…”

Section: Introductionmentioning

confidence: 99%

Link Budget Design for RF Line-of-Sight via Theoretical Propagation Prediction

Ibrahim¹,

Alsharekh²,

Almanee³

et al. 2019

IJCNS

View full text Add to dashboard Cite

Line-of-sight (LOS) link planning condition has been observed to have effects on the atmospheric factor which cause crucial signal loss. The main objective of the planning was to improve a set of a link using point to point condition to assist the performance in emerging its strategy for handling the fixed WLAN service. The purpose of this paper is to provide a quick description of various propagation loss mechanisms on Link Budget Tool (LBT). LBT is customized to create point to point link for local area network (LAN) through radio frequency range operating between 2.400 GHz and 5.800 GHz. This software is able to define the effect of signal loss and expected performances according to the distances between link propagation conditions based on a number of system parameters.

show abstract

“…In addition, MSs are free to move randomly within the coverage area which makes the network topology dynamic. The movement of MSs may not be free from transmission impairment [4], which in turn will lead to the loss of network Q 0 S. This work proposes to examine the applicability of different path loss models in the study area such as Hata, Cost 231, ECC-33, Ericson and Standard University Interim (SUI) models in suburban area in Nigeria, especially in Mubi in Adamawa State. The following changes shall be addressed, to compare the predicted (output of the models) and measured path losses, select and optimize the best fit model by determining the root mean square error (RMSE) between the predicted and measured path losses, modify the selected model using RMSE value and apply spline interpolation on the modified path loss to recover missing or eliminate the unwanted information in the radio path.…”

Section: Introductionmentioning

confidence: 99%

Selection and Optimization of Most Suitable Path Loss Prediction Model for Suburban City in Nigeria Using Spline Interpolation

Ali¹,

Silikwa²,

Ga-ya³

et al. 2018

JERR

View full text Add to dashboard Cite

Path loss is an attenuation of Global System for Mobile Communication (GSM) signal between Base Transceiver Station (BTS) and Mobile Station (MS). Path loss helps network engineers in planning, designing and implementing telecommunication networks. This work examines the applicability of Hata, COST 231, ECC – 33, Ericsson and SUI models in a medium city (Mubi) in Adamawa State, Nigeria. Root mean square error (RMSE) between the measured and the predicted losses (output of the models) is obtained as 7.632dB, 14.736dB, 10.593dB, 0.639dB and 23.491dB respectively. Ericsson model is found to have the least RMSE. Therefore, it is selected as the best fit model and modified. Furthermore, the modified model is optimized to recover missing or to eliminate unwanted information in the radio path using spline interpolation. The optimized model can be employed for the deployment of network resources in suburban areas of Nigeria, especially in Mubi town in Adamawa State, in order to significantly enhance GSM signal QoS. It is recommended that fuzzy logic and spline interpolation techniques may be integrated and employed to further minimize the error obtained in this work.

show abstract

Pathloss Measurements and Prediction using Statistical Models

Cited by 11 publications

References 7 publications

New Empirical Path Loss Model for 28 GHz and 38 GHz Millimeter Wave in Indoor Urban under Various Conditions

New Empirical Path Loss Model for 28 GHz and 38 GHz Millimeter Wave in Indoor Urban under Various Conditions

Link Budget Design for RF Line-of-Sight via Theoretical Propagation Prediction

Selection and Optimization of Most Suitable Path Loss Prediction Model for Suburban City in Nigeria Using Spline Interpolation

Contact Info

Product

Resources

About