Determination of GSM Signal Penetration Loss in some Selected Buildings in Rivers State, Nigeria

Elechi, Promise; Otasowie, PO

doi:10.4314/njt.v34i3.26

Cited by 9 publications

(8 citation statements)

References 4 publications

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“…[8] and [28], then proposed a model that is to cover the gaps which the Okumura-Hata model could not handle in terms of transmission parameters. The path loss model developed applies to base station antenna heights from 10 to 80 meters; base-to-terminal distances from 0.1 to 8km and distinct terrain categories of hilly/moderate to heavy tree density, hilly/light tree density or flat/moderate to heavy tree density and flat/light tree density.…”

Section: ) Erceg Et Al (1998) Modelmentioning

confidence: 99%

Assessment and Modeling of GSM Signal Propagation in Uyo, Nigeria

Orike¹,

Elechi²,

Ekanem³

2017

EJERS

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Abstract-High quality of service is a paramount concern in wireless networks. One of the strategies in achieving optimal performance is to use wireless empirical models to predict wireless link quality factors such as path loss and the received power in any given transmission domain with irregular terrain. The primary goal of this study is to develop a radio wave propagation model for Uyo metropolis. An assessment was carried out in three major roads within the city of Uyo in Akwa Ibom State, to determine the quality of GSM signal reception by measuring the signal field strength, magnetic field strength, and power density of the base transceiver stations. The measurements were carried out using radio frequency electromagnetic field strength meter over a distance of 2000 meters from the base stations. The results of the measurements were analysed and a path loss model was developed for Uyo using linear regression model. Three empirical models: Okumura-Hata model, COST-Hata model, and Egli model were also applied in predicting the path loss in Uyo and the results obtained were compared with the developed model for Uyo metropolis. The comparison showed that Route D model had a better comparison factor with the developed model while the Okumura-Hata and COST-Hata were almost the same with more loss as the distance increased. In all the measurements, the standard deviation was between 3.31 dB and 3.36 dB.

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Section: ) Erceg Et Al (1998) Modelmentioning

confidence: 99%

Assessment and Modeling of GSM Signal Propagation in Uyo, Nigeria

Orike¹,

Elechi²,

Ekanem³

2017

EJERS

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“…Urban area category is built up city or large town with large buildings and houses with two or more storey or larger village with close houses and tall, thickly grown trees. The Okumura model is expressed as [22], [28], and [24]:…”

Section: ) Log-distance Path Loss Modelmentioning

confidence: 99%

“…Predictions were made through series of graphs and the most important of which were approximated as a set of formulae by Hata in 1980 [6]. The thoroughness of the works by both Okumura and Hata made them the most widely quoted prediction model in macrocell environments [28] and [29]. They are often regarded as the standard used in judging new approaches [22].…”

Section: ) Hata Modelmentioning

confidence: 99%

Assessment and Modeling of GSM Signal Propagation in Uyo, Nigeria

Orike

Elechi

Ekanem³

2017

EJENG

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High quality of service is a paramount concern in wireless networks. One of the strategies in achieving optimal performance is to use wireless empirical models to predict wireless link quality factors such as path loss and the received power in any given transmission domain with irregular terrain. The primary goal of this study is to develop a radio wave propagation model for Uyo metropolis. An assessment was carried out in three major roads within the city of Uyo in Akwa Ibom State, to determine the quality of GSM signal reception by measuring the signal field strength, magnetic field strength, and power density of the base transceiver stations. The measurements were carried out using radio frequency electromagnetic field strength meter over a distance of 2000 meters from the base stations. The results of the measurements were analysed and a path loss model was developed for Uyo using linear regression model. Three empirical models: Okumura-Hata model, COST-Hata model, and Egli model were also applied in predicting the path loss in Uyo and the results obtained were compared with the developed model for Uyo metropolis. The comparison showed that Route D model had a better comparison factor with the developed model while the Okumura-Hata and COST-Hata were almost the same with more loss as the distance increased. In all the measurements, the standard deviation was between 3.31 dB and 3.36 dB.

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“…Generally, from -95 dBm and above, the signal strength is considered to be below average. However, from 100 dBm and above, the signal strength of the cell phone experiences some serious inconsistent service and weak signal reception (Elechi & Otasowie, 2015). The mobile phone signal booster will struggle with signal strength above 105 dBm.…”

Section: Introductionmentioning

confidence: 99%

Investigation of GSM Signal Strength in Rural Communities in the South-Eastern Region of Nigeria

Okoro

Iwuji

2019

ESJ

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This paper focuses on the investigation of GSM networks' signal strength coverage in rural communities in the South-Eastern region of Nigeria. The Network Cell Info Lite application installed in two Gionee M5 phones was used to carry out measurement of the signal strength received from the transmitting stations of various GSM networks. Signal strength obtained from the application was compared with the Gionee android inbuilt signal meter for authentication purposes. The signal strength measurements were conducted in Amaigbo from 18 th August to 26 th

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Determination of GSM Signal Penetration Loss in some Selected Buildings in Rivers State, Nigeria

Cited by 9 publications

References 4 publications

Assessment and Modeling of GSM Signal Propagation in Uyo, Nigeria

Assessment and Modeling of GSM Signal Propagation in Uyo, Nigeria

Assessment and Modeling of GSM Signal Propagation in Uyo, Nigeria

Investigation of GSM Signal Strength in Rural Communities in the South-Eastern Region of Nigeria

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