UAV Beam Alignment for Highly Mobile Millimeter Wave Communications

Zhang, Weizheng; Zhang, Wei; Jun, Wu

doi:10.1109/tvt.2020.2997740

Cited by 28 publications

(26 citation statements)

References 22 publications

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“…udu. Substitute the final expression of (52) in ( 49), we get the resultant expression for the first term of (45). Then, multiply the obtained expression with ( 47) to obtain the resultant expression for P c,T , given by (25).…”

Section: Appendix G Proof Of Theorem 12mentioning

confidence: 99%

Design and Analysis of Aerial-Terrestrial Network: A Joint Solution for Coverage and Rate

et al. 2021

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The exploitation of aerial base stations (A-BSs) in conjunction with terrestrial base stations (T-BSs) is envisioned as a promising solution to provide connectivity to devices and user-equipment (UE) in crowded situations (viz. in the sports event) and emergency situations (viz. in the disaster management). However, the use of A-BSs with existing terrestrial networks intensifies the inter-cell interference (ICI) to the devices and UEs, therefore leading to a degraded signal-to-interference-ratio (SIR). This paper addresses this issue by exploiting different radio access technology (RAT) (mmWave/microwave) for aerial and terrestrial networks. Indeed, the network connectivity is always a top priority for all applications. However, there are also some applications such as remote patient monitoring, and remote working, which requires both coverage and high data-rates. But, most of the existing research claims the trade-off between the coverage and the data-rate performance. Whereas this paper aims to improve coverage and rate simultaneously in an aerial-terrestrial networks by employing an optimal combination of mmWave and microwave RAT based on the proposed association strategy. The essential analysis of such an integrated network involves the evaluation of parameters based on the analytic model. Hence, this paper analytically obtains the coverage probability (CP) and average rate expressions for the proposed integrated aerial-terrestrial networks. The analysis is supported by probabilistic models-based simulations that agree closely with analytical results. The results claim that the proposed model leads to improved performance in terms of both CP and average rate. Also, the paper provides parametric analysis for CP and rate with A-BSs height and A-BSs density to enable its practical implementation in 5G/6G technologies.INDEX TERMS Aerial-terrestrial networks, millimeter-wave RAT, microwave RAT, coverage probability, average rate, stochastic geometry.

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Section: Appendix G Proof Of Theorem 12mentioning

confidence: 99%

Design and Analysis of Aerial-Terrestrial Network: A Joint Solution for Coverage and Rate

et al. 2021

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“…However, UAVenabled cellular architecture over mmWave frequency band has been recognized as one of the best solution for ondemand high data rate service. Therefore, the many existing works focused on UAV-assisted mmWave communications [24][25][26][27][28][29][30][31][32][33][34][35][36][37][38].…”

Section: Related Workmentioning

confidence: 99%

“…The authors of [36] investigated the rate performance, fairness, and their tradeoff in UAV swarm connected to mmWave cellular networks, where all UAVs are located in a 3D area and distributed according to a homogeneous PPP. The authors of [37] studied beamforming training and tracking for a UAVassisted mmWave system. They designed a beam training codebook according to the angular domain converted from the known location distribution of users and presented the two beam tracking methods in terms of both random and inertial user mobility to predict the beam direction.…”

Section: Related Workmentioning

confidence: 99%

Performance Optimization in UAV-Assisted Wireless Powered mmWave Networks for Emergency Communications

Gui

Jin

Deng

2021

Wireless Communications and Mobile Computing

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In this paper, we explore how a rotary-wing unmanned aerial vehicle (UAV) acts as an aerial millimeter wave (mmWave) base station to provide recharging service and radio access service in a postdisaster area with unknown user distribution. The addressed optimization problem is to find out the optimal path starting and ending at the same recharging point to cover a wider area under limited battery capacity, and it can be transformed to an extended multiarmed bandit (MAB) problem. We propose the two improved path planning algorithms to solve this optimization problem, which can improve the ability to explore the unknown user distribution. Simulation results show that, in terms of the total number of served user equipment (UE), the number of visited grids, the amount of data, the average throughput, and the battery capacity utilization level, one of our algorithms is superior to its corresponding comparison algorithm, while our other algorithm is superior to its corresponding comparison algorithm in terms of the number of visited grids.

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“…With the rapid development of high mobility communication fields such as unmanned aerial vehicles (UAVs) [16] and highspeed trains (HSTs) [17], the demand for channel estimation algorithms under mobile conditions is gradually increasing. Q.…”

Section: Introductionmentioning

confidence: 99%

MIMO Radar Aided mmWave Time-Varying Channel Estimation in MU-MIMO V2X Communications

Huang

Zhang

Gao

et al. 2021

IEEE Trans. Wireless Commun.

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Robust channel estimation in time-varying channels is used to guarantee the quality of communication services, especially for Vehicle-to-Everything (V2X) scenarios. To improve the channel estimation accuracy and reduce the pilot overhead, multi-input multi-output (MIMO) radar is deployed to assist millimeter wave (mmWave) channel estimation. In this paper, we propose a MIMO radar aided channel estimation scheme using deep learning (DL) for the uplink mmWave multiuser (MU)-MIMO communications. To allocate pilot resources reasonably, we design a transmission frame structure of joint radar module and communication module, which divides the estimation scheme into two stages, i.e., the arrival/departure (AoA/AoDs) estimation stage and the gain estimation stage. In view of the imperfections of array elements in practice, we propose an AoA/AoDs estimation algorithm based on subspace reconstruction in the AoA/AoDs estimation stage named two-step angle estimation (TSAE) algorithm. In the gain estimation stage, a DL based channel gain estimator is designed. An autoencoder combined with residual structure named residual denoising autoencoder (RDAE) is proposed to eliminate the noise on wireless signals, which is passed into the least square (LS) estimation module to obtain gains. Simulation results demonstrate that the MI-MO radar aided and DL-based channel estimator provides the efficient estimation performance of the high-mobility mmWave channel with fewer training resources. Index Terms-Deep learning (DL), millimeter wave (mmWave) communications, multiuser multi-input multi-output (MU-MIMO), MIMO radar, Vehicle-to-Everything (V2X).

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UAV Beam Alignment for Highly Mobile Millimeter Wave Communications

Cited by 28 publications

References 22 publications

Design and Analysis of Aerial-Terrestrial Network: A Joint Solution for Coverage and Rate

Design and Analysis of Aerial-Terrestrial Network: A Joint Solution for Coverage and Rate

Performance Optimization in UAV-Assisted Wireless Powered mmWave Networks for Emergency Communications

MIMO Radar Aided mmWave Time-Varying Channel Estimation in MU-MIMO V2X Communications

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