Suggested model for wireless communication in suburban environments with estimation of different channel models

Zakaria, Yahia; Ivanek, Lubomir; Urban, Zdeněk

doi:10.1109/elektro.2016.7512046

Cited by 5 publications

(3 citation statements)

References 8 publications

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“…The primary cause of a decrease in the energy density of an electromagnetic wave as it propagates through the environment is clearly signal pathway loss [21]. This description and conclusion agree with [22], [23].…”

Section: 𝑃𝐿 =supporting

confidence: 78%

Performance Evaluation of Channel Modeling and Path Loss Measurements for Wireless Communication Systems in Urban and Rural Territories. (Dept. E. Electronics)

Zakaria

Hamad

El-Hamid

et al. 2022

MEJ. Mansoura Engineering Journal

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over basic separations. Heinrich Rudolf Hertz discovered the propagation of electric and magnetic waves in 1886 [2]. Predicting frequency allocations, base station coverage areas, appropriate selection of the magnitude of the electric field, analysis of interference, and power level modification all benefit from correct path loss estimation [3], [4]. It is possible to determine a path loss prediction model for mobile propagation environments by comparing existing path loss with practical measured data.Furthermore, path loss is defined as the average attenuation of radio frequencies experienced by a sent signal when it

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Section: 𝑃𝐿 =supporting

confidence: 78%

Performance Evaluation of Channel Modeling and Path Loss Measurements for Wireless Communication Systems in Urban and Rural Territories. (Dept. E. Electronics)

Zakaria

Hamad

El-Hamid

et al. 2022

MEJ. Mansoura Engineering Journal

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“…As previously mentioned from results analysis, it can be noticed that the path loss is dominated by the free space loss and the building parameters function as added independent parameters to increase the overall model accuracy. Also, for both the building outlines and the foliage boundaries, the obtained value for the building attenuation decreases when the analyzed data are reduced to paths for each data set as described in (Fotheringham 2002;Zakaria and Urban 2016;Anderson 2003). According to the cases examined in this research, it can be observed that the value of path loss exponent (n) is higher in urban environment than in suburban environment.…”

Section: Logarithmic Regressionmentioning

confidence: 99%

Developed channel propagation models and path loss measurements for wireless communication systems using regression analysis techniques

et al. 2021

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Background The development of powerful and flexible management addresses is due to the improvement of deeply reliable gadgets and the advancement of the concept of cellular. The cellular principle was a major way of solving the wavelength crowding problem and the user capacity. It offered high capacity without major technological changes with limited allocation in spectrum. Wireless communication is an innovation in media transmission that allows remote transmission in all types of terrain between convenient gadgets. For estimating a transmitter 's radio coverage area, propagation models that anticipate the mean signal strength for an arbitrary transmitter–receiver separation distance are crucial as they are called large-scale propagation models so even though they define the average signal strength over long periods of time and large distances from the transmitter. Results Developed propagation models are presented according to the measured path loss values in exemplary urban and suburban areas at the operating frequency of 3.5 ghz by using the regression analysis. The measurements are implemented by using a spectrum analyzer FSH6 to get the channel response as shown in the stated tables and graphs. Based on the obtained results, it was observed that the path loss could be calculated as a function of distance and during the practical measurements 32 m was precise as a presumption for the break point distance. The values of path loss exponent (n) are defined and calculated for both of urban and suburban regions. Measurements results are analyzed and compared in order to study their influence for every specific environment. It was noticed that any radio signal will suffer attenuation when it travels from the transmitter to the receiver as a variety of various phenomena give rise to this radio path loss. Conclusions The interaction between both the electromagnetic radiation and the environment tends to decrease the quality of the signal being sent from the transmitter to the destination which causes the loss of the path. Propagation models are the basis for channel estimation, as they attempt to identify how a radio transmission changes from the transmitter to the receiver throughout its path. The gained results from this research will be supportive for the arrangement of network planners and researchers as proof and directory materials before future location establishment.

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“…The values of the path loss proponents for NTA Aba transmitters were determined and used to characterize TV signal propagation along with the distance breakpoint in the developed model. The mathematical model shown in Equation15was developed based on the results of this study's field measurements, while taking into consideration the fundamental expression for path loss shown in Equation 14 as shown byZakaria et al (2015;2016).…”

mentioning

confidence: 99%

Analysis and modeling of path loss for terrestrial television in Nigeria

Iwuji,

Okoro,

Amajama

et al. 2023

Int. J. Appl. Sci. Eng.

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The quality of services provided by television broadcasting corporations is significantly influenced by propagation path loss. The development of effective design and implementation of good quality signals is dependent on the accurate estimation of propagation path loss. Previous researchers have established several path losses models; however, these models cannot be applied to all situations and environments. The path losses of Nigeria Television Authority (NTA) Channel 6 Aba in Abia State, Nigeria were investigated in this study. A digital signal strength meter was used to measure the Received Signal Strength Level (RSSL) of the channel at 2 km intervals along 5 different routes around the base stations. Path loss values for each route were calculated using received signal strength. The obtained path loss was plotted against distance, and the result demonstrated that the path loss increases with distance along each of the routes. Further analysis of the variation of path loss with distance resulted in the development of a path loss model. To determine how accurate the model is in predicting path loss at the study sites, the developed model was compared with the measured path loss and some theoretical models for the NTA signals. Some statistical tools (RMSE, ME and SDE) were used to validate the developed model. Results also showed that the developed model predicted the path loss of NTA Aba signals very well, with an RMSE of 1.75. The existing theoretical path loss models considered overestimated the path loss values of NTA channel 6 Aba in the investigated environments, with RMSE values of 56.29, 75.68, 82.53, 79.03 and 72.61 for the FSPL, EGLI, okumura, Cost-231 Hata, and Cost-231 Walfisch-Ikegami models, respectively.

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Suggested model for wireless communication in suburban environments with estimation of different channel models

Cited by 5 publications

References 8 publications

Performance Evaluation of Channel Modeling and Path Loss Measurements for Wireless Communication Systems in Urban and Rural Territories. (Dept. E. Electronics)

Performance Evaluation of Channel Modeling and Path Loss Measurements for Wireless Communication Systems in Urban and Rural Territories. (Dept. E. Electronics)

Developed channel propagation models and path loss measurements for wireless communication systems using regression analysis techniques

Analysis and modeling of path loss for terrestrial television in Nigeria

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