Millimeter-Wave Propagation Measurement and Modeling in Indoor Corridor and Stairwell at 26 and 38 GHz

Shen, Yuyan; Shao, Yu; Liao, Xi; Zhang, Heng; Zhang, Jie

doi:10.1109/access.2021.3081822

Cited by 24 publications

(13 citation statements)

References 44 publications

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“…Thus, all the previous metrics results show the quality of the model's predictions for such environments. The reasons behind the accuracy of these models are: (1) The availability of training data since 80% of the measurement data was used to train the models. (2) Efficient input feature selection that considers crucial factors, such as the AoA and the Tx antenna's height for these indoor environments, in addition to essential factors, such as the Tx-Rx separation distance and the multi-frequency operating range of 14 to 22 GHz.…”

Section: Resultsmentioning

confidence: 99%

“…The raw datasets collected from the measurements were analyzed and cleaned to provide one reliable path loss value for each Tx-Rx separation distance, frequency, AoA, and Tx antenna height. Accordingly, the best features that lead to the optimum performance for the ML-based models adopted in this work are: (1) The distance between the transmitting and receiving antennas, which is the most crucial input feature that significantly affects the path loss values. (2) The operating frequency to provide multi-frequency path loss prediction models for the frequency range between 14 and 22 GHz.…”

Section: Data Preparationmentioning

confidence: 99%

“…Mobile communication has proliferated since its debut due to its flexibility and convenience. Due to the continuous evolution of communication technologies and the exponentially increasing demand for higher mobile data traffic, research has been focused on the frequency regime above 6 GHz to overcome the congestion of the previous bands (below 6 GHz) and to cope with the requirements of the fifth-generation (5G) wireless system and other high-speed multimedia services [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

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Comparative Analysis of Major Machine-Learning-Based Path Loss Models for Enclosed Indoor Channels

Elmezughi

Salih

Afullo

et al. 2022

Sensors

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Unlimited access to information and data sharing wherever and at any time for anyone and anything is a fundamental component of fifth-generation (5G) wireless communication and beyond. Therefore, it has become inevitable to exploit the super-high frequency (SHF) and millimeter-wave (mmWave) frequency bands for future wireless networks due to their attractive ability to provide extremely high data rates because of the availability of vast amounts of bandwidth. However, due to the characteristics and sensitivity of wireless signals to the propagation effects in these frequency bands, more accurate path loss prediction models are vital for the planning, evaluating, and optimizing future wireless communication networks. This paper presents and evaluates the performance of several well-known machine learning methods, including multiple linear regression (MLR), polynomial regression (PR), support vector regression (SVR), as well as the methods using decision trees (DT), random forests (RF), K-nearest neighbors (KNN), artificial neural networks (ANN), and artificial recurrent neural networks (RNN). RNNs are mainly based on long short-term memory (LSTM). The models are compared based on measurement data to provide the best fitting machine-learning-based path loss prediction models. The main results obtained from this study show that the best root-mean-square error (RMSE) performance is given by the ANN and RNN-LSTM methods, while the worst is for the MLR method. All the RMSE values for the given learning techniques are in the range of 0.0216 to 2.9008 dB. Furthermore, this work shows that the models (except for the MLR model) perform excellently in fitting actual measurement data for wireless communications in enclosed indoor environments since they provide R-squared and correlation values higher than 0.91 and 0.96, respectively. The paper shows that these learning methods could be used as accurate and stable models for predicting path loss in the mmWave frequency regime.

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Section: Resultsmentioning

confidence: 99%

Section: Data Preparationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Comparative Analysis of Major Machine-Learning-Based Path Loss Models for Enclosed Indoor Channels

Elmezughi

Salih

Afullo

et al. 2022

Sensors

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“…Indoor MIMO channel measurements in a lab at frequencies up to 30 GHz are presented in [38], concluding that the size of the antenna array influences the number of multipath components that are captured. Simulations and measurements in an office room for frequencies up to 30 GHz are presented in [39], and the indoor radio channel of a corridor and stairwell is characterized in [40] at 38 GHz. In [39], the authors draw the same conclusion as in [37], i.e., room furniture impacts the multipath characteristics of the channel.…”

Section: Introductionmentioning

confidence: 99%

V-Band Channel Modeling, Throughput Measurements, and Coverage Prediction for Indoor Residential Environments

et al. 2022

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With the increased resolution and frame rates of video recordings, in combination with the current evolution towards video-on-demand streaming services and the user expecting ubiquitous wireless connectivity, it is necessary to design wireless communication systems that allow high-rate data transfer. The large bandwidths that are available in the mmWave frequency band allow such high data rates. In this paper, we provide an experimental and simulated indoor residential radio channel model at V-band frequencies and perform packet error rate and throughput measurements at 60 GHz using IEEE 802.11ad transceivers. We compare the path loss and throughput measurements to simulations using a network performance prediction tool. The path loss measurement results using an omnidirectional transmit antenna correspond well to generic indoor mmWave channel models. Double-directional path loss measurements show that generic models underestimate path loss of non-Line-of-Sight (NLOS) links. A ray-launching algorithm is designed and validated, and used for IEEE 802.11ad throughput estimation based on link budget calculations. The link budget underestimates the achieved throughput, when comparing to adaptive-rate MCS selection in a commercial transceiver, based on the measured signal-to-noise ratio. Packet error rate measurements confirm that, even for NLOS links, throughputs exceeding 1 Gbps are possible.

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“…Thereby, VNA-based sounders are typically used indoors and over short distances. As in the STDCC case, these sounders have been widely used [20][21][22][23]. 7.…”

mentioning

confidence: 99%

A Wideband Radio Channel Sounder for Non-Stationary Channels: Design, Implementation and Testing

López-Valcárcel

Sánchez

2021

Electronics

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The increasing bandwidths and frequencies proposed for new mobile communications give rise to new challenges for system designers. Channel sounding and channel characterization are important tasks to provide useful information for the design of systems, protocols, and techniques to fight the propagation impairments. In this paper, we present a novel radio channel sounder capable of dealing with non-stationary channels. It can be operated in real-time and has a compact size to ease transport. For versatility and cost purposes, the core of the system is implemented in Field Programmable Gate Arrays (FPGAs). Three measurement campaigns have been conducted to illustrate the performance of the sounder in both static and non-static channels. In its current configuration, the sounder reaches an RF null-to-null bandwidth of 1 GHz, providing a delay resolution of 2 ns, a maximum measurable Doppler shift of 7.63 kHz, and 4.29 s of continuous acquisition time. A comparison with other channel sounders in the literature reveals that our proposal achieves a good combination of performance, cost, and size.

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Millimeter-Wave Propagation Measurement and Modeling in Indoor Corridor and Stairwell at 26 and 38 GHz

Cited by 24 publications

References 44 publications

Comparative Analysis of Major Machine-Learning-Based Path Loss Models for Enclosed Indoor Channels

Comparative Analysis of Major Machine-Learning-Based Path Loss Models for Enclosed Indoor Channels

V-Band Channel Modeling, Throughput Measurements, and Coverage Prediction for Indoor Residential Environments

A Wideband Radio Channel Sounder for Non-Stationary Channels: Design, Implementation and Testing

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