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Drones
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UAVs Communications for 6G
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UAVs Communications for 6G

A special issue of Drones (ISSN 2504-446X). This special issue belongs to the section "Drone Communications".

Deadline for manuscript submissions: closed (1 December 2023) | Viewed by 27316

Special Issue Editors

Dr. Sai Huang

E-Mail Website
Guest Editor
Department of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
Interests: fast detection and depth recognition of general wireless signals; UAV sensing and communications; radio frequency based drone identification
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Guan Gui

grade E-Mail Website
Guest Editor
College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
Interests: intelligent signal analysis, signal sensing and recognition, AI-based wireless techniques
Special Issues, Collections and Topics in MDPI journals
Dr. Xue Wang

E-Mail Website
Guest Editor
Department of Communication Engineering, Jilin University, Changchun 130012, China
Interests: intelligent terminal access and resource management of 5G and 6G; energy efficiency and latency research of wireless communication systems
Dr. Yuanyuan Yao

E-Mail Website
Guest Editor
School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing 100101, China
Interests: cooperative communication of UAV; RIS assisted communication; stochastic geometry and its applications in large-scale wireless networks; energy harvesting; intelligent radio resource allocation in 6G etc
Prof. Dr. Zhiyong Feng

E-Mail Website
Guest Editor
Department of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
Interests: UAV communications; integrated sensing and communications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

6G aims to provide ubiquitous wireless connectivity for the whole world. However, the demands for high-quality and ubiquitous wireless services impose enormous challenges to existing cellular networks. Unmanned aerial vehicles (UAVs), due to their agile maneuverability, can be dispatched as high-mobility aerial communication platforms to provide opportunistic line-of-sight links and further assist the terrestrial communications in 6G. Hence, integrating UAVs into 6G networks is a promising solution to achieve such goals. Integrated UAVs and 6G networks have numerous use cases, including base station (BS) offloading, swift service recovery after natural disasters, emergency response, rescue and search, information dissemination and data collection for Internet of Things (IoTs). However, one can never neglect the fact that the rapid deployment of high mobility UAV group may cause intra-system and inter-system interference to the original cellular communication networks. The quick and accurate interference detection and identification are the key technologies to guarantee normal operation of the integrated UAVs and 6G networks.

The integration of UAVs into 6G calls for a paradigm shift on the design of both cellular and UAV communications systems due to the high altitude and mobility of UAVs, the unique channel characteristics of UAV-ground links; the asymmetric quality of downlink and uplink data transmission; the stringent constraints imposed by the size, weight and power limitations of UAVs; as well as the intra-system and inter-system interference of the integrated networks. In order to provide users with smooth service experience and improve the resource utilization of integrated UAVs and 6G networks, the emergence of new theories, architectures and technologies such as the mechanisms of cognition for wireless and actual environment, data-driven intelligent learning mythologies, self-optimization and control need to be investigated and implemented. Therefore, the proposed Special Issue aims to bring together researchers, industry practitioners and individuals working in related areas to share their new ideas, latest findings and state-of-the-art results. Prospective authors with original research articles and reviews are invited to submit articles on the topic of “UAVs Communications and signal processing for 6G”. We look forward to receiving your contributions.

Dr. Sai Huang
Prof. Dr. Guan Gui
Dr. Xue Wang
Dr. Yuanyuan Yao
Prof. Dr. Zhiyong Feng
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Drones is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • UAV-assisted 6G communications
  • space–air–ground integrated network
  • integrated sensing and communications
  • trajectory optimization and resource allocation
  • physical layer security and radio monitoring

Published Papers (18 papers)

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Research

19 pages, 2756 KiB  
Article
Vehicle-to-Vehicle Based Autonomous Flight Coordination Control System for Safer Operation of Unmanned Aerial Vehicles
by Lin Shan, Ryu Miura, Takashi Matsuda, Miho Koshikawa, Huan-Bang Li and Takeshi Matsumura
Drones 2023, 7(11), 669; https://doi.org/10.3390/drones7110669 - 09 Nov 2023
Cited by 1 | Viewed by 1584
Abstract
The exponential growth of unmanned aerial vehicles (UAVs) or drones in recent years has raised concerns about their safe operation, especially in beyond-line-of-sight (BLOS) scenarios. Existing unmanned aircraft system traffic management (UTM) heavily relies on commercial communication networks, which may become ineffective if [...] Read more.
The exponential growth of unmanned aerial vehicles (UAVs) or drones in recent years has raised concerns about their safe operation, especially in beyond-line-of-sight (BLOS) scenarios. Existing unmanned aircraft system traffic management (UTM) heavily relies on commercial communication networks, which may become ineffective if network infrastructures are damaged or disabled. For this challenge, we propose a novel approach that leverages vehicle-to-vehicle (V2V) communications to enhance UAV safety and efficiency in UAV operations. In this study, we present a UAV information collection and sharing system named Drone Mapper®, enabled by V2V communications, so that UAVs can share their locations with each another as well as with the ground operation station. Additionally, we introduce an autonomous flight coordination control system (AFCCS) that augments UAV safety operations by providing two essential functionalities: UAV collision avoidance and UAV formation flight, both of which work based on V2V communications. To evaluate the performance of the developed AFCCS, we conducted comprehensive field experiments focusing on UAV collision avoidance and formation flight. The experimental results demonstrate the effectiveness of the proposed system and show seamless operations among multiple UAVs. Full article
(This article belongs to the Special Issue UAVs Communications for 6G)
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22 pages, 1775 KiB  
Article
A Non-Stationary Cluster-Based Channel Model for Low-Altitude Unmanned-Aerial-Vehicle-to-Vehicle Communications
by Zixv Su, Changzhen Li and Wei Chen
Drones 2023, 7(10), 640; https://doi.org/10.3390/drones7100640 - 18 Oct 2023
Viewed by 1502
Abstract
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. [...] Read more.
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. Full article
(This article belongs to the Special Issue UAVs Communications for 6G)
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17 pages, 688 KiB  
Article
On Joint Optimization of UAV-Assisted Covert Communication Systems with NOMA for Hydropower Internet of Things
by Zhenchun Le, Qing Xu, Yining Wang, Guowen Hao, Weifeng Pan, Yanlin Sun and Yuwen Qian
Drones 2023, 7(10), 610; https://doi.org/10.3390/drones7100610 - 27 Sep 2023
Viewed by 1057
Abstract
The intelligent terminals deployed in hydropower IoT can quickly sense the status of hydropower equipment, thus improving the efficiency of system control and operation. However, communication security between the base station and intelligent terminals challenges the IoT hydropower plant. In this paper, we [...] Read more.
The intelligent terminals deployed in hydropower IoT can quickly sense the status of hydropower equipment, thus improving the efficiency of system control and operation. However, communication security between the base station and intelligent terminals challenges the IoT hydropower plant. In this paper, we propose a UAV-assisted covert communication system (CCS), where a UAV acts as the base station to provide communication service to ground terminals monitored by malicious users. To improve access effectiveness, we adopt non-orthogonal multiple access (NOMA) for intelligent terminals to access the hydropower IoT. Since two devices can synchronously access the communication system with the NOMA scheme, we select one terminal to receive covert messages and the other to interfere with the malicious users to detect confidential communications. To maximize the covert rate, we formulate the optimization problem that jointly optimizes the transmit power, the altitude of the UAV, and trajectory under the constraints of covertness and the finite length of the transmission message block. Additionally, we transform the optimization problem into a geometric planning one, which is solved by a developed sequential geometric planning (SGP) approximation algorithm. Simulation results show the proposed algorithm can improve the covert rate compared to the traditional methods. Full article
(This article belongs to the Special Issue UAVs Communications for 6G)
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22 pages, 3831 KiB  
Article
MobileRaT: A Lightweight Radio Transformer Method for Automatic Modulation Classification in Drone Communication Systems
by Qinghe Zheng, Xinyu Tian, Zhiguo Yu, Yao Ding, Abdussalam Elhanashi, Sergio Saponara and Kidiyo Kpalma
Drones 2023, 7(10), 596; https://doi.org/10.3390/drones7100596 - 22 Sep 2023
Viewed by 1100
Abstract
Nowadays, automatic modulation classification (AMC) has become a key component of next-generation drone communication systems, which are crucial for improving communication efficiency in non-cooperative environments. The contradiction between the accuracy and efficiency of current methods hinders the practical application of AMC in drone [...] Read more.
Nowadays, automatic modulation classification (AMC) has become a key component of next-generation drone communication systems, which are crucial for improving communication efficiency in non-cooperative environments. The contradiction between the accuracy and efficiency of current methods hinders the practical application of AMC in drone communication systems. In this paper, we propose a real-time AMC method based on the lightweight mobile radio transformer (MobileRaT). The constructed radio transformer is trained iteratively, accompanied by pruning redundant weights based on information entropy, so it can learn robust modulation knowledge from multimodal signal representations for the AMC task. To the best of our knowledge, this is the first attempt in which the pruning technique and a lightweight transformer model are integrated and applied to processing temporal signals, ensuring AMC accuracy while also improving its inference efficiency. Finally, the experimental results—by comparing MobileRaT with a series of state-of-the-art methods based on two public datasets—have verified its superiority. Two models, MobileRaT-A and MobileRaT-B, were used to process RadioML 2018.01A and RadioML 2016.10A to achieve average AMC accuracies of 65.9% and 62.3% and the highest AMC accuracies of 98.4% and 99.2% at +18 dB and +14 dB, respectively. Ablation studies were conducted to demonstrate the robustness of MobileRaT to hyper-parameters and signal representations. All the experimental results indicate the adaptability of MobileRaT to communication conditions and that MobileRaT can be deployed on the receivers of drones to achieve air-to-air and air-to-ground cognitive communication in less demanding communication scenarios. Full article
(This article belongs to the Special Issue UAVs Communications for 6G)
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14 pages, 10267 KiB  
Article
Challenges in Inter-UAV 60 GHz Wireless Communication Utilizing Instantaneous Proximity Opportunities in Flight
by Ryosuke Isogai, Keitarou Kondou, Lin Shan, Takashi Matsuda, Ryu Miura, Satoshi Yasuda, Nobuyasu Shiga, Takeshi Matsumura and Yozo Shoji
Drones 2023, 7(9), 583; https://doi.org/10.3390/drones7090583 - 15 Sep 2023
Viewed by 1229
Abstract
Communication using millimeter wave (mmWave) and terahertz bands between unmanned aerial vehicles (UAVs) is a crucial technology for the realization of non-terrestrial networks envisioned for Beyond 5G. While these frequency bands offer remarkably high-speed transmission capabilities of tens of Gbps and above, they [...] Read more.
Communication using millimeter wave (mmWave) and terahertz bands between unmanned aerial vehicles (UAVs) is a crucial technology for the realization of non-terrestrial networks envisioned for Beyond 5G. While these frequency bands offer remarkably high-speed transmission capabilities of tens of Gbps and above, they possess strong directivity and limited communication range due to the requirement of high-gain antennas to compensate for substantial propagation loss. When a UAV employs radio of such a high-frequency band, the available communication time can be less than one second, and the feasibility of leveraging this ultra-narrow zone, which is only accessible for a short duration in a confined space, has not been investigated. This paper presents the theory behind the ultra-narrow zone in frequencies beyond mmWave and explores the data transfer characteristics at 60 GHz between two UAVs. We demonstrate the transmission of 120 MB of data within approximately 500 milliseconds utilizing the instantaneous proximity opportunity created as the UAVs pass each other. Additionally, we evaluate data transfer while the UAVs maintain a fixed distance, to sustain the 60 GHz link, successfully transmitting over 10 GB of data in the air with a throughput of approximately 5 Gbps. Full article
(This article belongs to the Special Issue UAVs Communications for 6G)
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18 pages, 960 KiB  
Article
A Deep Learning-Based Multi-Signal Radio Spectrum Monitoring Method for UAV Communication
by Changbo Hou, Dingyi Fu, Zhichao Zhou and Xiangyu Wu
Drones 2023, 7(8), 511; https://doi.org/10.3390/drones7080511 - 03 Aug 2023
Viewed by 1115
Abstract
Unmanned aerial vehicles (UAVs), relying on wireless communication, are inevitably influenced by the complex electromagnetic environment, attributed to the development of wireless communication technology. The modulation information of signals can assist in identifying device information and interference in the environment, which is significant [...] Read more.
Unmanned aerial vehicles (UAVs), relying on wireless communication, are inevitably influenced by the complex electromagnetic environment, attributed to the development of wireless communication technology. The modulation information of signals can assist in identifying device information and interference in the environment, which is significant for UAV communication environment monitoring. Therefore, in scenarios involving the communication of UAVs, it is necessary to find out how to perform the spectrum monitoring method to obtain the modulation information. Most existing methods are unsuitable for scenarios where multiple signals appear in the same spectrum sequence or do not use an end-to-end structure. Firstly, we established a spectrum dataset to simulate the UAV communication environment and developed a label method. Then, detection networks were employed to extract the presence and location information of signals in the spectrum. Finally, decision-level fusion was used to combine the output results of multiple nodes. Five modulation types, including ASK, FSK, 16QAM, DSB-SC, and SSB, were used to simulate different signal sources in the communication environment. Accuracy, recall, and F1 score were used as evaluation metrics. The networks were tested at different signal-to-noise ratios (SNRs). Among the different modulation types, FSK exhibits the most stable recognition performance across different models. The proposed method is of great significance for wireless radio spectrum monitoring in complex electromagnetic environments and is adaptable to scenarios where multiple receivers are used in vast terrains, providing a deep learning-based approach to radio monitoring solutions for UAV communication. Full article
(This article belongs to the Special Issue UAVs Communications for 6G)
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17 pages, 2061 KiB  
Article
Study of Power and Trajectory Optimization in UAV Systems Regarding THz Band Communications with Different Fading Channels
by Muhammet Ali Karabulut
Drones 2023, 7(8), 500; https://doi.org/10.3390/drones7080500 - 31 Jul 2023
Cited by 1 | Viewed by 834
Abstract
Researchers are interested in unmanned aerial vehicles (UAVs) because they have many uses in current 5G and future 6G networks and are safer than human-operated vehicles. Terahertz (THz)-band communications are a possible option in 6G for fast communication. THz wireless communication between UAVs [...] Read more.
Researchers are interested in unmanned aerial vehicles (UAVs) because they have many uses in current 5G and future 6G networks and are safer than human-operated vehicles. Terahertz (THz)-band communications are a possible option in 6G for fast communication. THz wireless communication between UAVs is taken into consideration in this work. Different fading channels, which are significant influencing factors in THz communication channel modeling, are used to analyze the performance of UAV communications in THz networks. Consideration must be made to the structure, wireless channel parameters, and transmission characteristics when evaluating the performance of wireless technology. Nakagami-m, Rician, Weibull, and Rayleigh fading channels are all taken into consideration, along with log-normal fading. Moreover, an optimization algorithm for the THz channel is presented, which is meant to minimize transmission power by optimizing the trajectory of uplink and downlink transmissions between the UAV and users. The equations of the UAV locations and the transmission power optimization of each user are derived. Analytical formulations regarding capacity, outage probability, and bit error rate (BER) are generated when performance-influencing factors are taken into account. The analytical analysis is supported by the numerical results that are provided. Full article
(This article belongs to the Special Issue UAVs Communications for 6G)
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17 pages, 1395 KiB  
Article
Two Low-Complexity Efficient Beamformers for an IRS- and UAV-Aided Directional Modulation Network
by Yeqing Lin, Feng Shu, Yuxiang Zheng, Jing Liu, Rongen Dong, Xun Chen, Yue Wu, Shihao Yan and Jiangzhou Wang
Drones 2023, 7(8), 489; https://doi.org/10.3390/drones7080489 - 26 Jul 2023
Viewed by 894
Abstract
As excellent tools for aiding communication, an intelligent reflecting surface (IRS) and an unmanned aerial vehicle (UAV) can extend the coverage area, remove the blind area, and achieve a dramatic rate improvement. In this paper, we improve the secrecy rate (SR) performance of [...] Read more.
As excellent tools for aiding communication, an intelligent reflecting surface (IRS) and an unmanned aerial vehicle (UAV) can extend the coverage area, remove the blind area, and achieve a dramatic rate improvement. In this paper, we improve the secrecy rate (SR) performance of directional modulation (DM) networks using an IRS and UAV in combination. To fully explore the benefits of the IRS and UAV, two efficient methods are proposed to enhance the SR performance. The first approach computes the confidential message (CM) beamforming vector by maximizing the SR, and the signal-to-leakage-noise ratio (SLNR) method is used to optimize the IRS phase shift matrix (PSM), which is called Max-SR-SLNR. To reduce the computational complexity, the CM, artificial noise (AN) beamforming, and IRS phase shift design are independently designed in the following method. The CM beamforming vector is constructed based on the maximum ratio transmission (MRT) criteria along the channel from Alice-to-IRS, the AN beamforming vector is designed by null-space projection (NSP) on the remaining two channels, and the PSM of the IRS is directly given by the phase alignment (PA) method. This method is called the MRT-NSP-PA. The simulation results show that the SR performance of the Max-SR-SLNR method outperforms the MRT-NSP-PA method in the cases of small-scale and medium-scale IRSs, and the latter approaches the former in performance as the IRS tends to a larger scale. Full article
(This article belongs to the Special Issue UAVs Communications for 6G)
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26 pages, 1277 KiB  
Article
Towards the Designing of Low-Latency SAGIN: Ground-to-UAV Communications over Interference Channel
by Sudhanshu Arya, Jingda Yang and Ying Wang
Drones 2023, 7(7), 479; https://doi.org/10.3390/drones7070479 - 20 Jul 2023
Cited by 7 | Viewed by 1163
Abstract
We present a novel and first-of-its-kind information-theoretic framework for the key design consideration and implementation of a ground-to-unmanned Aerial Vehicle (UAV) (G2U) communication network with an aim to minimize end-to-end transmission delay in the presence of interference in Space-Air-Ground Integrated Networks (SAGIN). To [...] Read more.
We present a novel and first-of-its-kind information-theoretic framework for the key design consideration and implementation of a ground-to-unmanned Aerial Vehicle (UAV) (G2U) communication network with an aim to minimize end-to-end transmission delay in the presence of interference in Space-Air-Ground Integrated Networks (SAGIN). To characterize the transmission delay, we utilize Fano’s inequality and derive the tight upper bound for the capacity for the G2U uplink channel in the presence of interference, noise, and potential jamming. In addition, as a function of the location information of the UAV, a tight lower bound on the transmit power is obtained subject to the reliability constraint and the maximum delay threshold. Furthermore, a relay UAV in the dual-hop relay mode, with amplify-and-forward (AF) protocol, is considered, for which we jointly obtain the optimal positions of the relay and the receiver UAVs in the presence of interference, with straight-line, circular, and helical trajectories as UAV tracing. Interestingly, increasing the power gives a negligible gain in terms of delay minimization, though may greatly enhance the outage performance. Moreover, we prove that there exists an optimal height that minimizes the end-to-end transmission delay in the presence of interference. We show the interesting result of the delay analysis. In particular, it is shown that receiver location and the end-to-end signal-to-noise power ratio play a critical role in end-to-end latency. For instance, with the transmitter location fixed to (0, 0, 0) and the interferer location set to (0, 500 m, 0), the latency generally increases with increasing the receiver’s vertical height (z-axis). With the receiver’s horizontal coordinates, i.e., (xR, yR) set to (0, 0) reducing the receiver’s height from 200 m to 50 m decreases the delay latency (codeword length) by more than 30% for an interference-limited channel. Whereas, for an interference channel with a signal-to-noise power ratio equal to 30 dB, the latency decreases by approximately 2%. The proposed framework can be used in practice by a network controller as a system parameters selection criteria, where among a set of parameters, the parameters leading to the lowest transmission latency can be incorporated into the transmission. The based analysis further set the baseline assessment when applying Command and Control (C2) standards to mission-critical G2U and UAV-to-UAV (U2U) services. Full article
(This article belongs to the Special Issue UAVs Communications for 6G)
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16 pages, 2215 KiB  
Article
MCST Scheme for UAV Systems over LoRa Networks
by Aung Thura Phyo Khun, Lin Shan, Yuto Lim and Yasuo Tan
Drones 2023, 7(6), 371; https://doi.org/10.3390/drones7060371 - 02 Jun 2023
Cited by 2 | Viewed by 1316
Abstract
In recent years, low-power wide-area network (LPWAN) has received widespread popularity with long-range and wide-area communication at low power for the Internet of Things (IoT) systems. Among many vendors of LPWAN, long-range low-power wireless communications, also called LoRa, is one of the competing [...] Read more.
In recent years, low-power wide-area network (LPWAN) has received widespread popularity with long-range and wide-area communication at low power for the Internet of Things (IoT) systems. Among many vendors of LPWAN, long-range low-power wireless communications, also called LoRa, is one of the competing standards and is well known in both academia and industrial communities as an emerging research area. Among the LoRa applications, unmanned aerial vehicles (UAV) systems are emerging with the benefits of extended battery life and a long communication range. In this paper, we investigate the network capacity with the mixture of concurrent and sequential transmission (MCST) scheme over LoRa networks. From the simulation results, it can be seen that MCST is suitable for implementation in the LoRa network. Specifically, MCST can achieve higher throughput with low transmission latency and energy consumption compared to the existing CSMA approach LoRa MAC. Besides, we also propose a modified MCST over the LoRa (mMCST/LoRa) scheme to mitigate the transmission latency further. The simulation results reveal a better performance in terms of throughput, latency and energy consumption, regardless of the frame payload size and the number of nodes in the network. Full article
(This article belongs to the Special Issue UAVs Communications for 6G)
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19 pages, 1208 KiB  
Article
Joint Beamforming and Phase Shift Design for Hybrid IRS and UAV-Aided Directional Modulation Networks
by Rongen Dong, Hangjia He, Feng Shu, Qi Zhang, Riqing Chen, Shihao Yan and Jiangzhou Wang
Drones 2023, 7(6), 364; https://doi.org/10.3390/drones7060364 - 30 May 2023
Cited by 1 | Viewed by 994
Abstract
Recently, intelligent reflecting surfaces (IRSs) and unmanned aerial vehicles (UAVs) have been integrated into wireless communication systems to enhance the performance of air–ground transmission. To balance performance, cost, and power consumption well, a hybrid IRS and UAV-assisted directional modulation (DM) network is investigated [...] Read more.
Recently, intelligent reflecting surfaces (IRSs) and unmanned aerial vehicles (UAVs) have been integrated into wireless communication systems to enhance the performance of air–ground transmission. To balance performance, cost, and power consumption well, a hybrid IRS and UAV-assisted directional modulation (DM) network is investigated in this paper in which the hybrid IRS consisted of passive and active reflecting elements. We aimed to maximize the achievable rate by jointly designing the beamforming and phase shift matrix (PSM) of the hybrid IRS subject to the power and unit-modulus constraints of passive IRS phase shifts. To solve the non-convex optimization problem, a high-performance scheme based on successive convex approximation and fractional programming (FP) called the maximal signal-to-noise ratio (SNR)-FP (Max-SNR-FP) is proposed. Given its high complexity, we propose a low-complexity maximal SNR-equal amplitude reflecting (EAR) (Max-SNR-EAR) scheme based on the maximal signal-to-leakage-noise ratio method, and the criteria of phase alignment and EAR. Given that the active and passive IRS phase shift matrices of both schemes are optimized separately, to investigate the effect of jointly optimizing them to improve the achievable rate, a maximal SNR majorization-minimization (MM) (Max-SNR-MM) scheme using the MM criterion to design the IRS PSM is proposed. Simulation results show that the rates harvested by the three proposed methods were slightly lower than those of the active IRS with higher power consumption, which were 35% higher than those of no IRS and random phase IRS, while passive IRS achieved only about a 17% rate gain over the latter. Moreover, compared with the Max-SNR-FP, the proposed Max-SNR-EAR and Max-SNR-MM methods caused obvious complexity degradation at the price of slight performance loss. Full article
(This article belongs to the Special Issue UAVs Communications for 6G)
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20 pages, 1068 KiB  
Article
Two Rapid Power Iterative DOA Estimators for UAV Emitter Using Massive/Ultra-Massive Receive Array
by Yiwen Chen, Qijuan Jie, Yiqiao Zhang, Feng Shu, Xichao Zhan, Shihao Yan, Wenlong Cai, Xuehui Wang, Zhongwen Sun, Peng Zhang and Peng Chen
Drones 2023, 7(6), 361; https://doi.org/10.3390/drones7060361 - 30 May 2023
Cited by 1 | Viewed by 1049
Abstract
To provide rapid direction finding (DF) for unmanned aerial vehicle (UAV) emitters in future wireless networks, a low-complexity direction of arrival (DOA) estimation architecture for massive multiple-input multiple-output (MIMO) receiver arrays is constructed. In this paper, we propose two strategies to address the [...] Read more.
To provide rapid direction finding (DF) for unmanned aerial vehicle (UAV) emitters in future wireless networks, a low-complexity direction of arrival (DOA) estimation architecture for massive multiple-input multiple-output (MIMO) receiver arrays is constructed. In this paper, we propose two strategies to address the extremely high complexity caused by eigenvalue decomposition of the received signal covariance matrix. Firstly, a rapid power iterative rotational invariance (RPI-RI) method is proposed, which adopts the signal subspace generated by power iteration to obtain the final direction estimation through rotational invariance between subarrays. RPI-RI causes a significant complexity reduction at the cost of a substantial performance loss. In order to further reduce the complexity and provide good directional measurement results, the rapid power iterative polynomial rooting (RPI-PR) method is proposed, which utilizes the noise subspace combined with the polynomial solution method to obtain the optimal direction estimation. In addition, the influence of initial vector selection on convergence in the power iteration is analyzed, especially when the initial vector is orthogonal to the incident wave. Simulation results show that the two proposed methods outperform the conventional DOA estimation methods in terms of computational complexity. In particular, the RPI-PR method achieves more than two orders of magnitude lower complexity than conventional methods and achieves performance close to the Cramér–Rao Lower Bound (CRLB). Moreover, it is verified that the initial vector and the relative error have a significant impact on the performance with respect to the computational complexity. Full article
(This article belongs to the Special Issue UAVs Communications for 6G)
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15 pages, 1397 KiB  
Article
Hybrid Data Augmentation and Dual-Stream Spatiotemporal Fusion Neural Network for Automatic Modulation Classification in Drone Communications
by An Gong, Xingyu Zhang, Yu Wang, Yongan Zhang and Mengyan Li
Drones 2023, 7(6), 346; https://doi.org/10.3390/drones7060346 - 25 May 2023
Cited by 2 | Viewed by 1106
Abstract
Automatic modulation classification (AMC) is one of the most important technologies in various communication systems, including drone communications. It can be applied to confirm the legitimacy of access devices, help drone systems better identify and track signals from other communication devices, and prevent [...] Read more.
Automatic modulation classification (AMC) is one of the most important technologies in various communication systems, including drone communications. It can be applied to confirm the legitimacy of access devices, help drone systems better identify and track signals from other communication devices, and prevent drone interference to ensure the safety and reliability of communication. However, the classification performance of previously proposed AMC approaches still needs to be improved. In this study, a dual-stream spatiotemporal fusion neural network (DSSFNN)-based AMC approach is proposed to enhance the classification accuracy for the purpose of aiding drone communication because SDDFNN can effectively mine spatiotemporal features from modulation signals through residual modules, long-short term memory (LSTM) modules, and attention mechanisms. In addition, a novel hybrid data augmentation method based on phase shift and self-perturbation is introduced to further improve performance and avoid overfitting. The experimental results demonstrate that the proposed AMC approach can achieve an average classification accuracy of 63.44%, and the maximum accuracy can reach 95.01% at SNR = 10 dB, which outperforms the previously proposed methods. Full article
(This article belongs to the Special Issue UAVs Communications for 6G)
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15 pages, 888 KiB  
Article
Low-Complexity Three-Dimensional AOA-Cross Geometric Center Localization Methods via Multi-UAV Network
by Baihua Shi, Yifan Li, Guilu Wu, Riqing Chen, Shihao Yan and Feng Shu
Drones 2023, 7(5), 318; https://doi.org/10.3390/drones7050318 - 12 May 2023
Viewed by 1652
Abstract
The angle of arrival (AOA) is widely used to locate a wireless signal emitter in unmanned aerial vehicle (UAV) localization. Compared with received signal strength (RSS) and time of arrival (TOA), AOA has higher accuracy and is not sensitive to the time synchronization [...] Read more.
The angle of arrival (AOA) is widely used to locate a wireless signal emitter in unmanned aerial vehicle (UAV) localization. Compared with received signal strength (RSS) and time of arrival (TOA), AOA has higher accuracy and is not sensitive to the time synchronization of the distributed sensors. However, there are few works focusing on three-dimensional (3-D) scenarios. Furthermore, although the maximum likelihood estimator (MLE) has a relatively high performance, its computational complexity is ultra-high. Therefore, it is hard to employ it in practical applications. This paper proposed two center of inscribed sphere-based methods for 3-D AOA positioning via multiple UAVs. The first method could estimate the source position and angle measurement noise at the same time by seeking the center of an inscribed sphere, called the CIS. Firstly, every sensor measures two angles, the azimuth angle and the elevation angle. Based on that, two planes are constructed. Then, the estimated values of the source position and the angle noise are achieved by seeking the center and radius of the corresponding inscribed sphere. Deleting the estimation of the radius, the second algorithm, called MSD-LS, is born. It is not able to estimate angle noise but has lower computational complexity. Theoretical analysis and simulation results show that proposed methods could approach the Cramér–Rao lower bound (CRLB) and have lower complexity than the MLE. Full article
(This article belongs to the Special Issue UAVs Communications for 6G)
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14 pages, 615 KiB  
Article
A Novel Collision Avoidance Strategy with D2D Communications for UAV Systems
by Lin Shan, Huan-Bang Li, Ryu Miura, Takashi Matsuda and Takeshi Matsumura
Drones 2023, 7(5), 283; https://doi.org/10.3390/drones7050283 - 22 Apr 2023
Cited by 5 | Viewed by 1320
Abstract
In recent years, safety operation issues related to the autonomous flight of unmanned aerial vehicles (UAVs) have become popular research and development topics worldwide. Among all UAV applications, multiple UAV-related applications are emerging due to the integration of UAVs into 6G networks, which [...] Read more.
In recent years, safety operation issues related to the autonomous flight of unmanned aerial vehicles (UAVs) have become popular research and development topics worldwide. Among all UAV applications, multiple UAV-related applications are emerging due to the integration of UAVs into 6G networks, which is an important topic for next-generation wireless communication systems. For multiple UAV applications, flight safety among UAVs is the most significant issue. Therefore, collision avoidance for UAVs has become an emerging topic in UAV-related research. In the past, although many UAV collision avoidance methods have been proposed, there is still a probability of other problems, such as no possible avoidance route and unmanaged UAVs that are without centralized control, which both result in an unpredictable risk of collisions. In this study, we investigate the current existing methods and propose novel collision avoidance methods based on the elastic collision principle. To verify the performance of the proposed methods, we also conduct simulations in this paper to demonstrate their effectiveness. From the simulation results, it can be seen that the proposed methods can effectively perform collision avoidance for multiple UAVs. Specifically, using the proposed methods, all UAVs can reach their destination points within reasonable time resources without any collision, validating the effectiveness of the proposed methods. Full article
(This article belongs to the Special Issue UAVs Communications for 6G)
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14 pages, 3531 KiB  
Article
Digital Self-Interference Cancellation for Full-Duplex UAV Communication System over Time-Varying Channels
by Lu Tian, Chenrui Shi and Zhan Xu
Drones 2023, 7(3), 151; https://doi.org/10.3390/drones7030151 - 22 Feb 2023
Cited by 1 | Viewed by 1528
Abstract
Full-duplex unmanned aerial vehicle (UAV) communication systems are characterized by mobility, so the self-interference (SI) channel characteristics change over time constantly. In full-duplex UAV communication systems, the difficulty is to eliminate SI in time-varying channels. In this paper, we propose a pilot-aid digital [...] Read more.
Full-duplex unmanned aerial vehicle (UAV) communication systems are characterized by mobility, so the self-interference (SI) channel characteristics change over time constantly. In full-duplex UAV communication systems, the difficulty is to eliminate SI in time-varying channels. In this paper, we propose a pilot-aid digital self-interference cancellation (SIC) method. First, the pilot is inserted into the data sequence uniformly, and the time-varying SI is modeled as a linear non-causal function. Then, the time-varying SI channel is estimated by the discrete prolate spheroidal basis expansion model (BEM). The error of block edge channel estimation is reduced by cross-block interpolation. The result of channel estimation is convolved with the transmitted data to obtain the reconstructed SI, which is subtracted from the received signal to achieve SIC. The simulation results show that the SIC performance of the proposed method outperforms the dichotomous coordinate descent recursive least square (DCD-RLS) and normalized least mean square (NLMS) algorithms. When the interference to noise ratio (INR) is 25 dB, the performance index normalized least mean square (NMSE) is reduced by 5.5 dB and 4 dB compared with DCD-RLS and NLMS algorithms, which can eliminate SI to the noise floor, and the advantage becomes more obvious as the INR increases. Full article
(This article belongs to the Special Issue UAVs Communications for 6G)
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13 pages, 747 KiB  
Article
Compressed Sensing-Based Genetic Markov Localization for Mobile Transmitters
by Sai Huang, Yuqing Chai, Shanchuan Ying, Shuo Chang and Nan Xia
Drones 2023, 7(1), 56; https://doi.org/10.3390/drones7010056 - 13 Jan 2023
Viewed by 1196
Abstract
With the strengths of quickness, low cost, and adaptability, unmanned aerial vehicle (UAV) communication is widely utilized in the next-generation wireless network. However, some risks and hidden dangers such as UAV “black flight” disturbances, attacks, and spying incidents lead to the necessity of [...] Read more.
With the strengths of quickness, low cost, and adaptability, unmanned aerial vehicle (UAV) communication is widely utilized in the next-generation wireless network. However, some risks and hidden dangers such as UAV “black flight” disturbances, attacks, and spying incidents lead to the necessity of the real-time supervision of UAVs. A compressed sensing-based genetic Markov localization method is proposed in this paper for two-dimensional trajectory tracking of the mobile transmitter in a finite domain, which consists of three modules: the multi-station sampling module, the reconstruction module, and the localization module. In the multi-station sampling module, multiple stations are deployed to receive the signal transmitted by the UAV using compressed sensing, and the motion model of the mobile transmitter is the constant turn rate and acceleration (CTRA) model. In the reconstruction module, we propose a direct reconstruction method to extract the joint cross-spatial spectrum. In the genetic Markov localization module, we propose a two-step localization method to genetically correct the inaccurate points in the preliminary results and generate the tracking result. Extensive simulations are conducted to verify the effectiveness of the proposed method. The results show that the proposed method is superior to the particle filter method and the Markov Monte Carlo method at all sampling moments. Specifically, when SNR = 15dB, the root-mean-square error (RMSE) of the proposed method is 39% and 60% lower than that of the other two methods, respectively. Moreover, under the premise that the RMSE of the localization result is less than 30 m, the reconstruction module can reduce the running time of the proposed method by 33.3%. Full article
(This article belongs to the Special Issue UAVs Communications for 6G)
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15 pages, 896 KiB  
Article
NOMA and UAV Scheduling for Ultra-Reliable and Low-Latency Communications
by Xiaowu Liu, Xihan Xu and Kan Yu
Drones 2023, 7(1), 41; https://doi.org/10.3390/drones7010041 - 06 Jan 2023
Cited by 2 | Viewed by 1613
Abstract
Ultra-reliable and low-latency communications (uRLLC) has received great attention in the study of wireless communication for it can provide high network performance in terms of reliability and latency. However, the reliability requirements of uRLLC require further investigation due to the inherent openness of [...] Read more.
Ultra-reliable and low-latency communications (uRLLC) has received great attention in the study of wireless communication for it can provide high network performance in terms of reliability and latency. However, the reliability requirements of uRLLC require further investigation due to the inherent openness of the wireless channel. Different from the previous reliable contributions that focused on the retransmission mechanism, in this paper, we consider scenarios with the interference of multiple UAVs. We establish an analytical framework of the packet error rate (PER) for an air-to-ground (A2G) channel. In this framework, the cellular users are allocated to different UAVs according to their minimum path loss with the aim of minimizing the PER. Furthermore, a wireless link scheduling algorithm is proposed to enhance the reliability between the UAV and cellular user. Simulated results show that, under the same power and channel block length level, our proposed non-orthogonal multiple access (NOMA) scheduling scheme has the best performance. Full article
(This article belongs to the Special Issue UAVs Communications for 6G)
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