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ISSN: 2321-9653
Estd : 2013
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Ijraset Journal For Research in Applied Science and Engineering Technology

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To Develop a Model for 4g LTE and Predictable 5G at 3500 Mhz that Would Predict the Path Loss for the Environment in Semi-Urban or Mixture of Urban and Rural Surroundings at Specific Geographical Locations

Authors: Suryashree Pandey, Abhinandan Sarkar

DOI Link: https://doi.org/10.22214/ijraset.2022.42001

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Abstract

In wireless communication, a planned network is given by the path loss model. Link budgeting, coverage prediction, and system performance optimization are indispensable in developing an accurate, simple, and general path loss model. To predict path loss in a particular environment each type of path loss propagation model is designed, it may be inaccurate in another different environment. In this paper, we are trying to predict a path loss model of Durgapur considering a particular place with a mixture of high-rise buildings, sub-urban, open, and foliage environments. For this proposal, the model area has been divided into twelve sectors taking 30° sectoring of radii 5 km and applying the path loss model for the calculation of path loss.

Introduction

I. INTRODUCTION

The attenuation of an electromagnetic wave is described by path loss. As the distance between the transmitter & receiver increases the radio wave signal strength also diminishes. To forecast the received power level for a specified coverage area by propagation model [1]. Empirical models contribute a statistical description of the relationship between path loss & propagation parameters. The parameters are frequency, antenna separation distance, and antenna heights. However, parameters of the empirical model are delivered from measured data in a particular structure. Before fitting the propagation model, it is required to divide the area into cells; we have divided the total area into 12 sections taking 5 km radii with 30° of sectoring. This given cell area consists of a different environment, each of which consists of a different environment, each of which contributes to signal strength loss. These given cells may consist of any one or more of the following environments [2] the human-made structure in an open area, in a suburban area, in an urban & in a rural area, natural terrain, flat terrain, hilly area, forest, & grasslands. The results of path loss generated from the prediction will depend upon the combination of the above factors, which make the cell geography. After the path loss levels are obtained, they are plotted against various parameters like angle, distance, etc.

II. REVIEW OF PATH LOSS PREDICTION FORMULATION

In the field of path loss propagation models, several studies have been completed where good results are obtained. All these studies are very important and play a vital role in wireless network planning. In [3] authors gave a brief introduction to loss models, concluding that each model is suitable for a specific environment. While [4] has analyzed and compared the path loss values of the selected models in different environments.

III. SELECTION OF CELL SITE

For path loss modeling, for example, a place was taken by Rajendranath College of the polytechnic, near Gopalpur, Durgapur-12.

IV. RESULT AND DISCUSSION

For example which place we have considered is a mixture environment (like some portion open, foliage, suburban, urban and high rise buildings).In Fig-3, we have taken 12 sectors of 30°, depicted in black color each. All sections are the combination of two or more environments. We use the red line for the foliage area, the blue line indicates the suburban area ,the yellow line for the open space area, and the green line indicates high rise building area.

Conclusion

We have predicted a path loss propagation model for a mixture of semi-urban, open & foliage areas in and around Durgapur. We observed different path loss values coming depending on various environment areas. Path loss prediction has a considerable impact on the planning and deployment of the wireless network. We hope this paper is going to serve as a reference for existing service providers.

References

[1] Östlin, E.; Zepernick, H.J.; Suzuki, H. Macrocell path-loss prediction using artificial neural networks. IEEE Trans. Veh. Technol. 2010, 59, 2735–2747. [CrossRef] [2] W.C.Y Lee, Mobile CellularTelecommuniactions, 2nd Edition, McGrawHill International Editions. [3] K. J. Parmar and D. V. D. Nimavat 2015, \"Comparative Analysis of Path Loss Propagation Models in Radio Communication,\" International Journal of Innovative Research in Computer and Communication Engineering, vol. 3, pp. 840-844. [4] Y. Zakaria, J. Hosek, and J. Misurec 2015, \"Path Loss Measurements for Wireless Communication in Urban and Rural Environments,\" American Journal of Engineering and Applied Sciences, vol. [5] Theodore S. Rappaport, Wireless Communications: Principles and Practice, 2nd Edition.

Copyright

Copyright © 2022 Suryashree Pandey, Abhinandan Sarkar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Authors : Suryashree Pandey-Sarkar

Paper Id : IJRASET42001

Publish Date : 2022-04-29

ISSN : 2321-9653

Publisher Name : IJRASET

DOI Link : Click Here

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International Journal for Research in Applied Science and Engineering Technology (IJRASET) is an international peer reviewed, online journal published for the enhancement of research in various disciplines of Applied Science & Engineering Technologies.

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