Full length articleAchievable rate of UAV-based communication with uniform circular arrays in Ricean fading
Introduction
Future wireless communication systems are envisioned to offer ubiquitous and sustainable high data-rate communication services [1], [2], [3]. Recently, aerial communication systems based on unmanned aerial vehicles (UAVs) has attracted more and more attention due to it could provide high maneuverability and fast flexible deployment of communication infrastructure in the design of future communication systems. The UAVs deployed with on-board wireless transceivers can fly over the target area and enjoy high mobility, the wireless channels are typically modeled via the Ricean fading because line-of-sight (LoS) and scatter components exist in wireless transmission environment [4], [5], [6]. Therefore, the achievable rate analysis of UAV-based communication systems under Ricean fading becomes a problem of practical relevance.
In the design of wireless communication systems, a lot of research about UAV-based communication transceivers were focus on uniform linear arrays (ULAs) at the base station (BS) [7], [8], [9]. In practical setup, when the transceivers is installed with ULAs and equipped with a very large antenna arrays, it will leads to the physical size become huge, which is challenge to the deployment of UAV-based communication infrastructure [10], [11], [12]. To handle this issue, the UAV-based communication systems is expected to deploy with the uniform plane antenna array [13], such as L-shaped antenna arrays, uniform circular antenna arrays (UCA), and parallel antenna arrays, which achieves the three-dimensional (3D) beamforming and cuts down the physical space. To reap the benefits of using uniform plane antenna array at the UAV’s transceivers, we will now review the relevant state-of-the-art in the UAV-based MIMO communication. For instance, the authors of [14] studied the efficient deployment of UAV-based MIMO communication, which aims to maximize system’s performance and the wireless networks’s coverage. The work in [15] presented a system model for UAV-based communications. The authors in [16], [17] reported that the LoS links from the UAV and users’ terminals play dominant role in short-distance. By applying user scheduling algorithm in various UAV-based wireless networks, the performance of UAV-based MIMO communication system can be efficiently improved. In [18], the authors presented a novel framework for trajectory optimization and energy-efficient UAV-based communication. The work in [19] investigated the joint optimization of user scheduling and UAV trajectory, which aims to enhance the achievable rate of system. As a general comment, most issues pertaining to the achievable rate of UAV-based MIMO communication under LoS scenario have been largely and extensively characterized. Apart from that, some recent investigations have analyzed the SE performance in the UAV-based MIMO communication under Rayleigh fading. To the maximum achievable sum-rate, linear precoding becomes a effective way, but the main challenge is that the transmitting terminal master the exact channel state information (CSI) [20], [21]. Hence, the research of statistical channel state information for multiuser massive MIMO system is of premier significance under wireless transmission. This is because the perfect CSI is hard to be attained from users terminal, but can be easily attained at the UAV’s transceivers. Fortunately, the authors in [22] proposed an excellent SE-SDMA scheme by utilizing statistical channel state information. The advantage of this scheme lies in that it not only can obtain the optimal achievable rate of systems with SCSI at the UAV’s transceivers, but also can acquire the ideal CSI at the users, Therefore, leaving the SE-SDMA scheme for UAV-based MIMO communication have been treated as an effective suboptimal technique.
Beside the technical challenges mentioned above, antenna array configuration also is the important factor in the UAV-based wireless communication systems in practice. For the conventional MIMO system, the base station is usually equipped with ULAs configuration [23]. as the number of antenna elements grows large enough (formed as massive MIMO system [24], [25]). The fundamental problem of placing a massive number of antennas in a confined space, can be addressed by deploying the uniform plane antenna array. For instant, the antenna elements of uniform rectangular plane antenna arrays (URPA) can be arranged at the both horizontally and vertically direction In addition, compared with the ULAs configuration, the UCAs configuration has more advantages such as the ability to utilize the azimuth-elevation angles and the intrinsic symmetric structure in the azimuth coverage of 360 degrees, lower mutual coupling, more compact structure [26], so more and more researchers have paid attention to UCAs configuration in future wireless communications. The authors in [27] gave the closed-form lower bound expression of achievable downlink sum-rate of multiuser MIMO system equipped with the UCA configuration, but it just consider the LoS scenario. The work in [28] investigated the achievable sum rate of massive MIMO system under time-varying Rayleigh channel. However, the achievable rate of massive MIMO system with UCAs configuration has not been well studied for the three-dimensional spatial channel model. Naturally, deep investigation of the UCA configuration is very essential, while analyzing the achievable rate of UAV-based communication systems under Ricean fading.
From the above discussion, we clear sense that a straightforward and exact theoretical result for UAV-based MIMO systems with Ricean fading is missing from the open literature. This paper presents a general analytic framework for studying the achievable rate of UAV-based communications with a UCA configuration. The main contributions of this paper are summarized as follows:
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By utilizing the statistical channel state information and adopting general Ricean fading channel, there is a need for a new SE-SDMA scheme that can be used to analyze the performance of UAV-based communications with the UCA configuration. We exploit an effective SE-SDMA scheme with only the knowledge of the CSI at the UAV’s transceivers.
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Based on this scheme, a suboptimal beamforming precoder is proposed, which is on the basis of the signal-to-interference-and-noise ratio (SINR) in [29]. This precoder is used for deriving a closed-form formula of the achievable ergodic rate. Secondly, we thus investigate the achievable rate of UAV-based communication system with UCAs under Ricean fading and an exact expression on the achievable rate is given.
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Our results showcase that the achievable sum-rate tends to a saturation value in the high signal-to-noise ratio regime. Furthermore, we find that the high Ricean -factor and the small values of inner product between different channel statistical vector are contribute to the achievable sum-rate of the UAV-based communication system.
Notation: Vector and Matrix are expressed as in lowercase and uppercase boldface, and denote the conjugate transpose and transpose, respectively, and stand for Euclidean norm and the absolute value, respectively, is the identity matrix, denotes the phase of a complex number , represents a complex Gaussian distribution with mean and variance while a Gaussian distribution with mean and variance denotes as ; the expectation of a random variable is denoted as while the matrix determinant and trace by and .
Section snippets
System model
In this section, we describe a signal transmission model and UAV-based communication channel model, and then we further introduce the achievable rate of the UAV-based MIMO system. Some key assumptions made for such system model are also highlighted.
Spectral efficiency analysis
In this section, by utilizing the concept of interference power, we propose the suboptimal beamforming precoder with the knowledge of CSI at the UAV’s transceivers, which shall be used for deriving a closed-form formula for the achievable ergodic rate.
Numerical results
In this section, we consider a single cellular network, where two users are uniformly distributed in the circle-shaped cell. The Monte-Carlo simulations are provided to verify the above theoretical analysis. We assume that the number of antennas at the UAV’s transceivers is set to , the radius of the UCAs is and the channel mean vectors of the user and are randomly generated according to (3). For concision, the user and have the same Ricean -factor and is denoted
Conclusion
This paper investigated the achievable rate of UAV-based communication under Ricean fading, where the transceivers of UAV is equipped with UCA configuration. By exploiting an effective SE-SDMA scheme with only the knowledge of the CSI at the UAV’s transceivers. We derived an exact expression on the achievable rate of UAV-based communication systems with UCA configuration, where the transceivers adopts the channel response vector as the beamforming precoder. Based on the derived theoretical
Acknowledgments
This work was supported in part by the National Natural Science Foundation of China under Grants 61801132 and 61801192, the Natural Science Foundation of Guangdong Province of China under Grant 2018A030310338, and the Project of Educational Commission of Guangdong Province of China under Grant 2017KQNCX155, the Open Research Fund of National Mobile Communications Research Laboratory, Southeast University, China Grant 2017D10, the Tencent “Rhinoceros Birds” Scientific Research Foundation for
Weijie Tan received the M.S. in communication and information system from Communication University of China, Beijing, China, in 2011. From 2016 to 2017, he was a visiting researcher with the Audio Analysis Lab, AD:MT, Aalborg University, Denmark. Currently, he is working towards the Ph.D. degree in the Northwestern Polytechnical University, China. His research interests include array signal processing, communication signal processing, parameter estimation, sparse signal representation and
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2022, Physical CommunicationCitation Excerpt :In [28], the authors have analyzed ergodic capacity in downlink transmission SATN with multi-user proportional fair scheduling. Different from related works [7,28], in which only one user is scheduled in a time slot in multi-user SATN, an effective space division multiple access (SDMA) transmission scheme has been proposed [29–32]. SDMA is a principle of radio resource sharing that separates communication channels in space.
Spectral efficiency in non-terrestrial heterogeneous networks with spectrum underlay access
2021, Physical CommunicationCitation Excerpt :The small-scale characterization at different altitudes of ABSs has been investigated in [12–15], and the RMS delay spread in order of a few hundred nanoseconds has been measured. Utilizing LABSs as ABSs and relays have fascinated many researchers [16–18]. In [16], a LABS equipped with circular array antennas has been used to serve two users with Space Division Multiple Access (SDMA) scheme, and a beamforming matrix has been designed for ergodic sum-rate maximization.
Performance analysis for multi-user integrated satellite and UAV cooperative networks
2019, Physical CommunicationCitation Excerpt :An UAV-enabled wireless relay model was studied and the analytical expression of the OP was obtained and optimized in [23]. In [24], the authors studied the multi-antenna UAV transmission system and derived exact achievable rate. More recently, the integrated satellite and UAV cooperative network (ISUCN) has drawn significantly attention due to its potential to build a reliable communication network with wide coverage and high data rate in emergencies, especially when unexpected natural disaster makes the terrestrial infrastructure paralyzed or totally destroyed in [25].
Weijie Tan received the M.S. in communication and information system from Communication University of China, Beijing, China, in 2011. From 2016 to 2017, he was a visiting researcher with the Audio Analysis Lab, AD:MT, Aalborg University, Denmark. Currently, he is working towards the Ph.D. degree in the Northwestern Polytechnical University, China. His research interests include array signal processing, communication signal processing, parameter estimation, sparse signal representation and convex optimization.
Shidang Li is with the School of Physics and Electronic Engineering, Jiangsu Normal University, Xuzhou 221116, China. He received the Ph.D. degrees in information and telecommunication engineering from the Southeast University, Nanjing, China, in 2016. He is currently an Assistant Professor with the School of Physics and Electronic Engineering, Jiangsu Normal University. His current research interests include energy harvesting, physical-layer security, and interference alignment.
Chunlong He received the M.S. degree in communication and information science from Southwest Jiaotong University, Chengdu, China, in 2010 and the Ph.D. degree from Southeast University, Nanjing, China, in 2014. From September 2012 to September 2014, he was a Visiting Student with the School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA. Since 2015, he has been with the College of Information Engineering, Shenzhen University, where he is currently an Assistant Professor. His research interests include communication and signal processing, green communication systems, channel estimation algorithms, and limited feedback techniques. Dr. He is a member of the Institute of Electronics, Information, and Communication Engineering. He is currently an Associate Editor of IEEE Access.
Weiqiang Tan received the Ph.D. degree from the National Mobile Communications Research Laboratory, Southeast University, Nanjing, China, in 2017; The M.S. degree from Chengdu University of Information Technology, China, in 2013. From 2016 to 2017, he was a visiting Ph.D student with the School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, United Kingdom. He is currently a lecturer at the school of Computer Science and Educational Software, Guangzhou University, Guangzhou. His research interests include massive MIMO and Millimeter wave wireless communication.
Xiaobo Gu received his B.S degree in communication engineering and M.S. degree in signal and information processing from the University of Electronic Science and Technology of China, Chengdu, China in 2008 and 2011 respectively, and his Ph.D degree in communication and information system from Beihang University, Beijing, China, in 2016. From 2016 to 2018, he was with the China Southern Power Grid, Guangzhou, China as an Engineer. Since Sep. 2018, he has been with Guangdong University of Technology, Guangzhou, China, as a lecturer. His current research interests include time synchronization and positioning in wireless communication networks.
Zheng Shi received the B.S. degree in communication engineering from Anhui Normal University, China, in 2010, the M.S. degree in communication and information system from the Nanjing University of Posts and Telecommunications, China, in 2013, and the Ph.D. degree in electrical and computer engineering from the University of Macau, Macau, in 2017. Since 2017, he has been with the School of Electrical and Information Engineering, Jinan University, where he is currently an Assistant Professor. His research interests include hybrid automatic repeat request protocols, cooperative communications, full-duplex communications, non-orthogonal multiple access, and millimeter-wave and heterogeneous wireless networks.