A Mixed-Bouncing Based Non-Stationary Model for 6G Massive MIMO mmWave UAV Channels

Bai, Lu; Huang, Ziwei; Cui, Lizhen; Feng, Tao; Cheng, Xiang

doi:10.1109/tcomm.2022.3204032

Cited by 7 publications

(6 citation statements)

References 38 publications

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“…In [22], an RT-based Monte-Carlo method was conducted to analyze and evaluate UAV AG channel model performance. In stochastic channel modeling, geometry-based stochastic models (GBSMs) have been widely used, and the corresponding channel characteristics have been analyzed [23][24][25][26][27][28][29][30][31][32]. In [25], a novel non-stationary maritime UAV-to-ship GBSM was proposed.…”

Section: Introductionmentioning

confidence: 99%

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Channel Characterization and Modeling for 6G UAV-Assisted Emergency Communications in Complicated Mountainous Scenarios

Zhang,

Liu,

Huang

et al. 2023

Sensors

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Regarding the new demands and challenges of sixth-generation (6G) mobile communications, wireless networks are undergoing a significant shift from traditional terrestrial networks to space-air-ground-sea-integrated networks. Unmanned aerial vehicle (UAV) communications in complicated mountainous scenarios are typical applications and have practical implications, especially in emergency communications. In this paper, the ray-tracing (RT) method was applied to reconstruct the propagation scenario and then acquire the wireless channel data. Channel measurements are also conducted in real mountainous scenarios for verification. By setting different flight positions, trajectories, and altitudes, channel data in the millimeter wave (mmWave) band was obtained. Important statistical properties, such as the power delay profile (PDP), Rician K-factor, path loss (PL), root mean square (RMS) delay spread (DS), RMS angular spreads (ASs), and channel capacity were compared and analyzed. The effects of different frequency bands on channel characteristics at 3.5 GHz, 4.9 GHz, 28 GHz, and 38 GHz bands in mountainous scenarios were considered. Furthermore, the effects of extreme weather, especially different precipitation, on the channel characteristics were analyzed. The related results can provide fundamental support for the design and performance evaluation of future 6G UAV-assisted sensor networks in complicated mountainous scenarios.

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Section: Introductionmentioning

confidence: 99%

“…Based on an angular estimation algorithm, a novel UAV channel model for UAV AG communications was proposed in [29]. In [30], a hybrid hopping-based channel model was proposed to improve the model accuracy. In addition, time-space consistency and the impacts of UAV posture variation and fuselage scattering were considered in [31,32].…”

Section: Introductionmentioning

confidence: 99%

Channel Characterization and Modeling for 6G UAV-Assisted Emergency Communications in Complicated Mountainous Scenarios

Zhang,

Liu,

Huang

et al. 2023

Sensors

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“…Due to the notable advantages, the focus is increasingly shifting to cluster-based GBSMs. A certain number of literature has shown that an evolution algorithm is crucial for capturing the channel non-stationarity, and it is generally developed in the time, frequency, and space domain [31][32][33][34][35][36][37][38][39][40][41][42][43]. The evolution algorithm often depends on the birth-and-death (BD) process [31][32][33][34], which can be explained by the fact that clusters may be observable or unobservable for each antenna.…”

Section: Introductionmentioning

confidence: 99%

“…Bai et al develop a space-time (ST) BD algorithm based on the impact of UAV parameters on channels [39] and an improved space-time-frequency (STF) BD algorithm based on the frequency-dependent path gain [40]. Huang et al incorporate a novel correlated cluster method and K-means clustering algorithm into the BD algorithm [41] and they also propose a new hybrid method combining the parametric method and a visibility region (VR) approach [42].…”

Section: Introductionmentioning

confidence: 99%

“…In addition, due to the scarcity of research on UAV channels containing multiple types of clusters, there is a limited exploration of time evolution algorithms for different types of clusters and the impact of different types of clusters on UAV channels. Although an UAV channel considering SB and MB components is constructed in [41], it does not compare the channel characteristics of single clusters and twin clusters. The comparison of the characteristics of different clusters is vital for analyzing the contribution of different multipath components to the variation trend of statistical properties.…”

Section: Introductionmentioning

confidence: 99%

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A Non-Stationary Cluster-Based Channel Model for Low-Altitude Unmanned-Aerial-Vehicle-to-Vehicle Communications

Su,

Li,

Chen

2023

Drones

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Under the framework of sixth-generation (6G) wireless communications, the unmanned aerial vehicle (UAV) plays an irreplaceable role in a number of communication systems. In this paper, a novel cluster-based low-altitude UAV-to-vehicle (U2V) non-stationary channel model with uniform planar antenna arrays (UPAs) is proposed. In order to comprehensively model the scattering environment, both single and twin clusters are taken into account. A novel continuous cluster evolution algorithm that integrates time evolution and array evolution is developed to capture channel non-stationarity. In the proposed algorithm, the link between the time evolution of twin clusters and that of single clusters is established to regulate the temporal evolution trend. Moreover, an improved observable radius method is applied to UPAs for the first time to describe array evolution. Based on the combination of cluster evolution and time-variant channel parameters, some vital statistical properties are derived and analyzed, including space–time correlation function (ST-CF), angular power spectrum density (PSD), Doppler PSD, Doppler spread (DS), frequency correlation function (FCF), and delay spread (RS). The non-stationarity in the time, space, and frequency domain is captured. It demonstrates that the airspeed, density of scatterers within clusters, and carrier frequency have an impact on statistical properties. Furthermore, twin clusters have more flexible spatial characteristics with lower power than single clusters. These conclusions can provide assistance and reference for the design and deployment of 6G UAV communication systems.

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Three‐dimensional geometry‐based channel modeling and simulations for reconfigurable intelligent surface‐assisted uav‐to‐ground MIMO communications

Wang,

Chen,

Wang

et al. 2024

IET Communications

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Consisting of a large number of passive reflectors, reconfigurable intelligent surface (RIS) has gained traction as an approach to enhance communication quality. The specular reflection assumption is common when ideal conditions are considered. In this paper, an anomalous‐reflector model was found for each RIS reflection unit, deviating from the specular reflector assumption, and the impacts of the aperture area and radiation pattern of the RIS reflecting elements are taken into account. A three‐dimensional (3D) geometry‐based RIS‐assisted channel model is proposed for stochastic multiple‐input multiple‐output (MIMO) unmanned aerial vehicle (UAV)‐to‐ground communications. The RIS is deployed on an additional UAV in the proposed model, which assists the UAV transmitter for reflecting its own signals to the mobile receiver (MR) on the ground level, thereby boosting the quality of signal transmission. In order to achieve a perfect beam alignment towards the desired direction, the reflection phase is regulated by considering the propagation distances among UAV, RIS, and MR.

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A Mixed-Bouncing Based Non-Stationary Model for 6G Massive MIMO mmWave UAV Channels

Cited by 7 publications

References 38 publications

Channel Characterization and Modeling for 6G UAV-Assisted Emergency Communications in Complicated Mountainous Scenarios

Channel Characterization and Modeling for 6G UAV-Assisted Emergency Communications in Complicated Mountainous Scenarios

A Non-Stationary Cluster-Based Channel Model for Low-Altitude Unmanned-Aerial-Vehicle-to-Vehicle Communications

Three‐dimensional geometry‐based channel modeling and simulations for reconfigurable intelligent surface‐assisted uav‐to‐ground MIMO communications

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