2019•Unpublished venueRequires access

Short Term and Long Term Path Loss Estimation in Urban, SubUrban and Rural Areas

Ch. Usha Kumari, Padmavathi Kora, K. Meenakshi, K. Swaraja

Open publisher page 13 citations

Abstract

Planning and performance of any wireless channel in different environment is analysed by the path loss prediction models. In this paper the path-loss between the Base-Station (BS) and Mobile-Station (MS) for the Received-Signal-Strength (RSS) in different wireless environments is estimated. Non-isotropic antennas are used with different transmitter and receiver gains. A mathematical expression is proposed to compute path loss with antenna gains of 0.5 and 1 by varying the distance up to 1km. Then the path loss is optimized by introducing the path loss component that varies with environment. The path loss component is varied from 2 to 6. The shadowing effect is modelled by log-distance method. In this paper Gaussian random variable is considered with a mean zero and standard deviation is taken as 3dB. Simulation results show the path loss component increases by increasing the gain of antenna. The path loss is also calculated by IEEE 802.16d model and Hata-model. It is observed that as the gain of antenna decreases the path-loss increases and vice-versa. Path-loss also increases by distance and shadowing effects.

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What this paper is about

Planning and performance of any wireless channel in different environment is analysed by the path loss prediction models. In this paper the path-loss between the Base-Station (BS) and Mobile-Station (MS) for the Received-Signal-Strength (RSS) in different wireless environments is estimated. Non-isotropic antennas are used with different transmitter and receiver gains. A mathematical expression is proposed to compute path loss with antenna gains of 0.5 and 1 by varying the distance up to 1km. Then the path loss is optimized by introducing the path loss component that varies with environment. The path loss component is varied from 2 to 6. The shadowing effect is modelled by log-distance method. In this paper Gaussian random variable is considered with a mean zero and standard deviation is taken as 3dB. Simulation results show the path loss component increases by increasing the gain of antenna. The path loss is also calculated by IEEE 802.16d model and Hata-model. It is observed that as the gain of antenna decreases the path-loss increases and vice-versa. Path-loss also increases by distance and shadowing effects.

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Available abstract

Planning and performance of any wireless channel in different environment is analysed by the path loss prediction models. In this paper the path-loss between the Base-Station (BS) and Mobile-Station (MS) for the Received-Signal-Strength (RSS) in different wireless environments is estimated. Non-isotropic antennas are used with different transmitter and receiver gains. A mathematical expression is proposed to compute path loss with antenna gains of 0.5 and 1 by varying the distance up to 1km. Then the path loss is optimized by introducing the path loss component that varies with environment. The path loss component is varied from 2 to 6. The shadowing effect is modelled by log-distance method. In this paper Gaussian random variable is considered with a mean zero and standard deviation is taken as 3dB. Simulation results show the path loss component increases by increasing the gain of antenna. The path loss is also calculated by IEEE 802.16d model and Hata-model. It is observed that as the gain of antenna decreases the path-loss increases and vice-versa. Path-loss also increases by distance and shadowing effects.

Key concepts: Path loss, Log-distance path loss model, Antenna height considerations, Transmitter, Computer science, Shadow mapping, Antenna (radio), Telecommunications

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