An Inversion Propagation Model Using GA for Coverage Prediction of a Single Urban Cell in Wireless Network

2008 ◽  
Author(s):  
Y. Wang ◽  
G. Dang ◽  
Y. Si ◽  
H. Zhou
Keyword(s):  
Wireless Network ◽  
Propagation Model ◽  
Coverage Prediction

scholarly journals 4G Wireless network coverage prediction for operator “A” by using GIS  in Jeddah City: a case study of Al Nuzhah district: التنبؤ بتغطية أبراج شبكة الاتصالات اللاسلكية 4G للمشغل "أ" باستخدام نظم المعلومات الجغرافية في مدينة جدة (دراسة حالة حي النزهة)

2020 ◽  
Vol 4 (2) ◽  
Author(s):  
Noha Saeed Alhomrani, Sarra Al Habib Ouerghi
Keyword(s):  
Wireless Network ◽  
Communication Networks ◽  
Communication Systems ◽  
Propagation Model ◽  
Network Coverage ◽  
Network Efficiency ◽  
Jeddah City ◽  
4G Wireless ◽  
Coverage Prediction

Communication systems depend on cell tower signals which affect the quality and efficiency of communications networks. In this paper, a prediction network coverage of 4G wireless network for operator “A” in Al Nuzhah city has been elaborated. The main objective is, firstly, to come up with prediction network maps showing the quality of communication networks in the study area and to identify areas with good and bad coverage, in order to maintain and improve coverage through relocating cell towers and antennas, increasing their number, or through installing new ones in bad coverage areas. Another objective is to compare this output with actual network coverage efficiency. In this study, GIS programs were adopted to handle, manage, process and analyze spatial and attribute data. GIS extensions were used to design communication networks such as the Mentum-Planet program through which prediction network coverage was calculated and represented. Cell towers and sectors data was first collected and then processed to generate the 4G coverage network prediction for operator "A" based on propagation model (Q9). Results were later compared to the network efficiency generated by the Drive Test. It was found that the signal strength was between -95 and -75 db. About 24.2% and 75.8% of the studied area had medium and excellent network coverage, respectively. The Drive Test showed areas of poor network coverage distributed throughout the study area. This research concluded that use of GIS in communications reduces cost and time of implementation. It is highly recommended to include building heights in the propagation model as it affects the spread of communication waves, to increase cell towers in poor coverage areas, and to modify the propagation model to ensure quality of service and efficient coverage.

A Practical RF Propagation Model for Wireless Network Sensors

2009 ◽  
Author(s):  
Tsenka Stoyanova ◽  
Fotis Kerasiotis ◽  
Aggeliki Prayati ◽  
George Papadopoulos
Keyword(s):  
Wireless Network ◽  
Propagation Model ◽  
Rf Propagation

Simulation of Digital Radio Mondiale (DRM) Coverage Prediction – A study case with Radio Republik Indonesia (RRI)

2017 ◽  
Vol 4 (1) ◽  
pp. 32-36
Author(s):  
Nabila Husna Shabrina
Keyword(s):  
Service Planning ◽  
Propagation Model ◽  
System Specification ◽  
Theory Analysis ◽  
Digital Radio ◽  
Analysis And Design ◽  
Transmitter Power ◽  
Antenna Type ◽  
Radio Systems ◽  
Coverage Prediction

In this paper, DRM is applied for simulating coverage prediction in Radio Republik Indonesia (RRI). The proposed method is developed by simulating high frequency propagation from RRI Pro 3 transmitter with VOACAP online software. The simulation is undertaken in some different conditions. The variation of antenna type and transmitter power are observed in the simulation. The time of propagation also discussed to predict the coverage. The result shows that the variation of parameter influences the coverage result of DRM propagation in HF band. Changing the antenna type and time of propagation will make impact in the range of coverage while adding power transmitter gives insignificantly effect to the range of coverage. Keywords—DRM, Prediction Coverage, VOACAP REFERENCES [1] ITU R-REP-BS.2144-2009-PDF-E, “Planning parameters and coverage for Digital Radio Mondiale (DRM) broadcasting at frequencies below 30 MHz”, 2009. [2] M. J. Bradley, “Digital Radio Mondiale: System and Receivers”,Roke Manor Research Ltd, UK, 2003 [3] G. Prieto, I. Pichel, D. Guerra, P. Angueira, J.M. Matias, J.L. Ordiales, A. Arrinda, “Digital Radio Mondiale: Broadcasting and Reception”, IEEE Press, 2004. [4] DRM Features, available under http://www.drm.org [5] “Digital Radio Mondiale (DRM); System Specification,” European Telecommunication Standards Institute (ETSI), ETSI TS 101980, 2001. [6] D. Setiawan, “Alokasi Frekuensi, Kebijakan dan Perencanaan Spektrum Indonesia”, Departemen Komunikasi dan Informatika, 2010. [7] P.A Bradley, Th Dambold, P.Suessmann, “Propagation model for HF Radio Service Planning”, HF Radio Systems and Techniques, Conference Publication No 474 0 IEE, 2000. [8] J.J. Carr, “Practical Antenna Handbook 4th Edition”, McGraw Hill, 1990. [9] J.M Matias et al, “DRM (Digital Radio Mondiale) Local Coverage Tests Using the 26 Mhz Broadcasting Band”, IEEE Transactions on Broadcasting, Vol. 53, No. 1, August 2007. [10] C. A. Balanis, “Antenna Theory Analysis and Design”, 2nd ed, John Wiley & Sons, 2005. [11] Keputusan Direktorat Jendral Pos dan Telekomunikasi Nomor 85/DIRJEN/1999, “Spesifikasi Teknis Perangkat Telekomunikasi, Persyaratan Teknis Perangkat Radio Siaran”, Jakarta, 1999.

Using Spreadsheet Maps for the Placement of Low Altitude Platform (LAP) Wireless Network Nodes After Disasters

2021 ◽  
Vol 4 (1) ◽  
pp. 31-46
Author(s):  
Larry J. LeBlanc ◽  
Michael R. Bartolacci ◽  
Thomas A. Grossman
Keyword(s):  
Wireless Network ◽  
Network Connectivity ◽  
Propagation Model ◽  
Additional Contribution ◽  
Weight Restrictions ◽  
Network Nodes ◽  
Emergency Responders ◽  
Standard Models ◽  
Low Altitude ◽  
Fixed Wireless

Low altitude platform (LAP) architectures are an emerging platform for providing temporary wireless network connectivity to areas with a damaged fixed wireless network infrastructure. The authors propose a spreadsheet-based approach for practitioners to locate LAP nodes in the field. This approach does not require radio frequency propagation expertise and incorporates standard models to display the coverage areas for the placement of LAP aerial devices. The proposed tool allows the transmission range for a given aerial device to be visually optimized during deployment. The spreadsheet-based tool the authors are proposing is expressly suited for battery-powered LAP architecture devices with payload weight restrictions, such as those utilizing balloons or kites, that can be quickly deployed by emergency responders. An additional contribution of this work is the development of a hybrid propagation model for LAP device transmissions for deployments above 200 meters which is absent in the literature. This model is a linear combination of two existing models for free space radio propagation.

scholarly journals Enhanced Cost231 W.I. Propagation Model in Wireless Network

2011 ◽  
Vol 19 (6) ◽  
pp. 36-42 ◽  
Author(s):  
Hemant Kumar Sharma ◽  
Santosh Sahu ◽  
Sanjeev Sharma
Keyword(s):  
Wireless Network ◽  
Propagation Model
Sign in / Sign up

Export Citation Format

Share Document