Indoor Multi-wall Path Loss Model at 1.93 GHz

Li, Lun; Ibdah, Yazan; Ding, Yanwu; Eghbali, Homa; Muhaidat, Sami; Ma, Xu

doi:10.1109/milcom.2013.211

Cited by 13 publications

(5 citation statements)

References 7 publications

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“…The multiwall path-loss model has usually been used to analyze indoor electromagnetic wave propagation [ 23 , 24 , 25 ] from industrial plants [ 26 ], laboratory buildings [ 27 ], school buildings [ 28 ], and many others. This model is derived from one of the basic path-loss models for indoor environments—the one-slope model [ 29 ]—where the free-space path-loss term is introduced as follows:

where

reference pathloss, which is the path loss over 1 m distance; d is the distance between the transmitter and the receiver; and n is the path-loss exponent that indicates how fast the path loss increases with distance.…”

Section: Methodsmentioning

confidence: 99%

“…The multiwall path-loss model has usually been used to analyze indoor electromagnetic wave propagation [23][24][25] from industrial plants [26], laboratory buildings [27], school buildings [28], and many others. This model is derived from one of the basic path-loss models for indoor environments-the one-slope model [29]-where the free-space path-loss term is introduced as follows:…”

Section: The Multiwall Path-loss Model For Palm Oil Plantationsmentioning

confidence: 99%

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A Multiwall Path-Loss Prediction Model Using 433 MHz LoRa-WAN Frequency to Characterize Foliage’s Influence in a Malaysian Palm Oil Plantation Environment

Anzum

Habaebi

Islam

et al. 2022

Sensors

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Palm oil is the main cash crop of tropical Asia, and the implementation of LPWAN (low-power wide-area network) technologies for smart agriculture applications in palm oil plantations will benefit the palm oil industry in terms of making more revenue. This research attempts to characterize the LoRa 433 MHz frequency channels for the available spreading factors (SF7-SF12) and bandwidths (125 kHz, 250 kHz, and 500 kHz) for wireless sensor networks. The LoRa channel modeling in terms of path-loss calculation uses empirical measurements of RSS (received signal strength) in a palm oil plantation located in Selangor, Malaysia. In this research, about 1500 LoS (line-of-sight) and 300 NLoS (non-line-of-sight) propagation measurement data are collected for path-loss prediction modeling. Using the empirical data, a prediction model is constructed. The path-loss exponent for LoS propagation of the proposed prediction model is found to be 2.34 and 2.9 for 125–250 kHz bandwidth and 500 kHz bandwidth, respectively. Again, for the NLoS propagation links, the attenuation per trunk is found to be 7.58 dB, 7.04 dB, 5.35 dB, 5.02 dB, 5.01 dB, and 5 dB for SF7-SF12, and the attenuation per canopy is found to be 9.32 dB, 7.96 dB, 6.2 dB, 5.89 dB, 5.79 dB, and 5.45 dB for SF7-SF12. Moreover, the prediction model is found to be the better choice (mean RMSE 2.74 dB) in comparison to the empirical foliage loss models (Weissberger’s and ITU-R) to predict the path loss in palm oil plantations.

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where

Section: Methodsmentioning

confidence: 99%

Section: The Multiwall Path-loss Model For Palm Oil Plantationsmentioning

confidence: 99%

A Multiwall Path-Loss Prediction Model Using 433 MHz LoRa-WAN Frequency to Characterize Foliage’s Influence in a Malaysian Palm Oil Plantation Environment

Anzum

Habaebi

Islam

et al. 2022

Sensors

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show abstract

“…In [110,111], indoor models were proposed based on the two-slope model with compensation factor fit by the measurements. At the same time, a series of models were proposed based on the COST-231 multi-wall model for indoor [112,113] and home [114]. A log-distance path loss model is the extension of the Friis model and includes the random shadow effect caused by the signal being blocked by hills, trees, buildings, etc.…”

Section: Other Modelsmentioning

confidence: 99%

The Current Progress and Future Prospects of Path Loss Model for Terrestrial Radio Propagation

Wang,

Hao,

Yang

2023

Electronics

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The radio channel model is a major factor supporting the whole life cycle of the terrestrial radio system, including the demonstration, design, validation, operation, and so on. To improve the spectrum sharing and spectral efficiency in terrestrial radio services, we analyze three types of path loss models in detail: deterministic, empirical, and semi-empirical models, to meet the requirements of path loss modeling for supporting traditional band expansion and reuse. Then, we conduct a comparative analysis based on the characteristics of the current models. Furthermore, a preview of the future terrestrial path loss modeling methods is provided, including intelligent modeling processes and multi-model hybridization methods. Finally, we look forward to the potential technology that can be used in future wireless communication, such as terahertz communication, reconfigurable intelligent surface technology, and integrated communication and sensing technology. The above research can provide a reference for the development of terrestrial radio channel modeling, promoting the technologies of terrestrial channel modeling. We hope this paper will stimulate more interest in modeling terrestrial radio channels.

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“…Currently, wireless communication systems require the knowledge of the signal-to-noise ratio (SNR) in order to enhance the system transmission performance by using techniques including error correction coding, adaptive modulation, 1 power control, 2 multicast optimization, 3 ad-hoc network, 4 cognitive radio, 5-8 symbol detection, 9,10 path loss modeling, 11 etc. All of these techniques require measuring the communication link quality.…”

Section: Introductionmentioning

confidence: 99%

SINR estimation for SATCOM in the environment with jamming signals

Wang

Tian

et al. 2016

SPIE Proceedings

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In this paper we consider a problem of estimating the signal-to-interference-plus-noise ratio (SINR) for satellite transmission system in the presence of jamming signals. Additive white Gaussian noise (AWGN) channels are considered for baseband quadrature phase shift keying (QPSK) data transmission system. Two interference models are proposed with Gaussian or non-Gaussian interference signals in order to investigate the SINR for different satellite transmission jamming scenarios. Both non-data-aided moment-based and data-aided maximum likelihood SINR estimators are derived for the systems. The normalized mean square errors of the SINR estimation algorithms are examined by means of computer simulations. The numerical results show the robustness of derived SINR estimators. The development of the SINR estimators are applicable to a large number of applications utilizing satellite communication systems.

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Indoor Multi-wall Path Loss Model at 1.93 GHz

Cited by 13 publications

References 7 publications

A Multiwall Path-Loss Prediction Model Using 433 MHz LoRa-WAN Frequency to Characterize Foliage’s Influence in a Malaysian Palm Oil Plantation Environment

A Multiwall Path-Loss Prediction Model Using 433 MHz LoRa-WAN Frequency to Characterize Foliage’s Influence in a Malaysian Palm Oil Plantation Environment

The Current Progress and Future Prospects of Path Loss Model for Terrestrial Radio Propagation

SINR estimation for SATCOM in the environment with jamming signals

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