Path loss Prediction Models for Wireless Communication Channels and its Comparative Analysis

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International Journal of Engineering, Management & Sciences (IJEMS) ISSN-2348 –3733, Volume-2, Issue-3, March 2015

Path loss Prediction Models for Wireless Communication Channels and its Comparative Analysis Santosh Choudhary, Dinesh Kumar Dhaka  Abstract— The aim of this paper is investigate the performance of various path loss models in different environments for determination of the signal strength with respect to various frequency ranges and distance for wireless network. There are five path loss models, namely Free Space, Log-distance, Log-normal, Okumura/Hata, IEEE802.16d models. These models have been reviewed with different receiver antenna heights in urban, suburban and rural environments. Free space path loss model is used as reference value for produced the estimated results value. Then compare all estimated results of reviewed models with the reference model values. Hata model demonstrated good performance in terms of received signal strength or indirectly, reduction in path-loss. Log-normal model based on the shadowing effect while calculating the values of path-loss. IEEE802.16d model and log-normal model are similar. And it is a standard model used for the measurements of path-loss in sub-urban area. However, Hata model could be preferred due to better performance in terms of less path loss as compared with the results of reference model at lower receiver antenna heights for urban and open area environments. Index Terms— Path loss, Log-distance, Log-normal, Okumura/Hata.

I. INTRODUCTION The losses occurred in between transmitter and receiver is known as propagation path loss In wireless communication. Path loss is the unwanted reduction in power single which is transmitted. This path loss in different area like rural, urban, and suburban with the help of propagation path loss models are measured by author. The wireless channel environment is mainly govern the performance of wireless communication systems. Channel environment plays main role in wireless communication. So the foundation for the development of high performance and bandwidth-efficient wireless transmission technology is very important. In other words, the propagation of a radio wave is a complicated and less predictable process. There are three phenomenon that affects reflection, diffraction, and scattering, whose intensity varies with different environment s at different instances. Manuscript received March 22, 2015 Santosh Choudhary, M. Tech. Scholar, Rajasthan College of Engineering for Women, Jaipur Dinesh Kumar Dhaka, Asst. Professor, Rajasthan College of Engineering for Women, Jaipur

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Fading: A unique characteristic in a wireless channel is a phenomenon called ‘fading,’ the variation of the signal amplitude over time and frequency. Mainly two reason take into account for fading, multipath propagation, referred to as multi-path (induced) fading, or to shadowing from obstacles that affect the propagation of a radio wave, referred to as shadow fading.

Fig. 1 Path Loss, Shadowing and Multipath versus Distance Advantage of predicting model: By performing simulations calculated by propagation models over the area of demand, the change in the network coverage can be predicted. The more accurate the prediction model, easier it gets to develop the cellular network. II. VARIOUS PATH-LOSS MODELS These models can be broadly categorized into three types; empirical, deterministic and stochastic. A. Empirical models Empirical models are those based on observations and measurements alone. These models are mainly used to predict the path loss, rain-fade and multipath have also been proposed. Empirical models can be split into two subcategories namely, time dispersive and non-time dispersive. B. Deterministic models The deterministic models make use of the laws governing electromagnetic wave propagation to determine the received signal power at a particular location. Deterministic models often require a complete 3-D map of the propagation environment. An example of a deterministic model is a ray tracing model.

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