Centimeter and Millimeter-Wave Propagation Characteristics for Indoor Corridors: Results From Measurements and Models

Diba, Feyisa Debo; Samad, Abdus; Choi, Dong-You

doi:10.1109/access.2021.3130293

Cited by 7 publications

(4 citation statements)

References 35 publications

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“…In [10], motivated by the waveguiding effect, the authors have proposed a single-slope segment-wise path gain model for transmission along corridors at 28 GHz. In [11], to overcome channel complexity and timeconsuming measurements, a novel methodology using an artificial neural network (ANN) techniques in indoor corridors at 3.7 and 28 GHz has been studied. To improve path loss models for indoor corridors, in [12] the close-in (CI) free space reference distance model and the floating-intercept (FI) model were studied and optimized considering 14, 18, and 22 GHz measurements.…”

Section: Introductionmentioning

confidence: 99%

Towards Practical Path Loss Predictions in Indoor Corridors Considering 5G mmWave Three-Dimensional Measurements

Diago-Mosquera

Aragón‐Zavala

Rodríguez

2022

Antennas Wirel. Propag. Lett.

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Theoretical and empirical foundations of how radio waves behave in practical wireless channels need to be fully revisited for millimeter-wave (mmWave) frequencies so that fifthgeneration (5G) technologies may be successful. Kriging is an outstanding geostatistal interpolation technique that employs variography to understand the spatial variability of known samples at specific locations to predict unmeasured samples, based on the fact that there is an implied connection between the measured value and its location in space. The research we here report is aimed at validating the improvement in predictions when this tool is included for mmWave frequency path loss modeling in a long indoor corridor with break. In order to quantify the accuracy of the proposed methodology, it is compared with a wellestablished procedure described in the literature. Extensive pathloss measurements were collected through specialized narrowband sounders at 28 and 60 GHz. Spatially averaged power measurements using omnidirectional and directive antennas at different heights provided the empirical basis for the threedimensional (3D) Kriging-aided model. It was found that this method significantly improves the accuracy as it considers all the singularities and site-associated features that are implicit in measured samples. This is important to obtain a reliable path loss model for planning and deployment of mmWave wireless communication systems in indoor scenarios.

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Section: Introductionmentioning

confidence: 99%

Towards Practical Path Loss Predictions in Indoor Corridors Considering 5G mmWave Three-Dimensional Measurements

Diago-Mosquera

Aragón‐Zavala

Rodríguez

2022

Antennas Wirel. Propag. Lett.

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“…This study is the continuation of our previous study of path loss measurement [ 8 , 9 , 25 ] in closed indoor environments. In this study, we investigated a particular type of stairwell, a bent stairwell with a wall partition, at the campus of Chosun University in Gwangju, South Korea.…”

Section: Introductionmentioning

confidence: 78%

“…In the literature, different types of indoor environments such as corridor [ 8 ], hall [ 9 ], office [ 10 ], laboratory [ 11 ], indoor production site [ 12 ], and library [ 13 ] were proposed.…”

Section: Introductionmentioning

confidence: 99%

Path loss measurement and modeling of 5G network in emergency indoor stairwell at 3.7 and 28 GHz

Samad

Choi

2023

PLoS ONE

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Research on path loss in indoor stairwells for 5G networks is currently insufficient. However, the study of path loss in indoor staircases is essential for managing network traffic quality under typical and emergency conditions and for localization purpose. This study investigated radio propagation on a staircase where a wall separated the stairs from free space. A horn and an omnidirectional antenna were used to determine path loss. The measured path loss evaluated the close-in-free-space reference distance, alpha-beta model, close-in-free-space reference distance with frequency weighting, and alpha-beta-gamma model. These four models exhibited good compatibility with the measured average path loss. However, comparing the path loss distributions of the projected models revealed that the alpha-beta model exhibited 1.29 dB and 6.48 dB for respectively, at 3.7 GHz and 28 GHz bands. Furthermore, the path loss standard deviations obtained in this study were smaller than those reported in previous studies.

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“…For indoor scenarios, several research works have been conducted [15][16][17][18]. In [15], the authors proposed a method based on Neural Networks (NN) to estimate the radio frequency exposure generated by Wi-Fi sources in indoor scenarios.…”

Section: Related Work 21 Machine Learning For Path Loss Estimationmentioning

confidence: 99%

Indoor Genetic Algorithm-Based 5G Network Planning Using a Machine Learning Model for Path Loss Estimation

Santana

Alonso

Nieto³

et al. 2022

Applied Sciences

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Accurate wireless network planning is crucial for the deployment of new wireless services. This usually requires the consecutive evaluation of many candidate solutions, which is only feasible for simple path loss models, such as one-slope models or multi-wall models. However, such path loss models are quite straightforward and often do not deliver satisfactory estimations, eventually impacting the quality of the proposed network deployment. More advanced models, such as Indoor Dominant Path Loss models, are usually more accurate, but as their path loss calculation is much more time-consuming, it is no longer possible to evaluate a large set of candidate deployment solutions. Out of necessity, a heuristic network planning algorithm is then typically used, but the outcomes heavily depend on the quality of the heuristic. Therefore, this paper investigates the use of Machine Learning to approximate a complex 5G path loss model. The much lower calculation time allows using this model in a Genetic Algorithm-based network planning algorithm. The Machine Learning model is trained for two buildings and is validated on three other buildings, with a Mean Absolute Error below 3 dB. It is shown that the new approach is able to find a wireless network deployment solution with an equal, or smaller, amount of access points, while still providing the required coverage for at least 99.4% of the receiver locations and it does this 15 times faster. Unlike a heuristic approach, the proposed one also allows accounting for additional design criteria, such as maximal average received power throughout the building, or minimal exposure to radiofrequency signals in certain rooms.

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Centimeter and Millimeter-Wave Propagation Characteristics for Indoor Corridors: Results From Measurements and Models

Cited by 7 publications

References 35 publications

Towards Practical Path Loss Predictions in Indoor Corridors Considering 5G mmWave Three-Dimensional Measurements

Towards Practical Path Loss Predictions in Indoor Corridors Considering 5G mmWave Three-Dimensional Measurements

Path loss measurement and modeling of 5G network in emergency indoor stairwell at 3.7 and 28 GHz

Indoor Genetic Algorithm-Based 5G Network Planning Using a Machine Learning Model for Path Loss Estimation

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