Capacity of UAV-Enabled Multicast Channel: Joint Trajectory Design and Power Allocation

This paper studies an unmanned aerial vehicle (UAV)-enabled multicast channel, in which a UAV serves as a mobile transmitter to deliver common information to a set of $K$ ground users. We aim to characterize the capacity of this channel over a finite UAV communication period, subject to its maximum speed constraint and an average transmit power constraint. To achieve the capacity, the UAV should use a sufficiently long code that spans over its whole communication period. Accordingly, the multicast channel capacity is achieved via maximizing the minimum achievable time-averaged rates of the $K$ users, by jointly optimizing the UAV's trajectory and transmit power allocation over time. However, this problem is non-convex and difficult to be solved optimally. To tackle this problem, we first consider a relaxed problem by ignoring the maximum UAV speed constraint, and obtain its globally optimal solution via the Lagrange dual method. The optimal solution reveals that the UAV should hover above a finite number of ground locations, with the optimal hovering duration and transmit power at each location. Next, based on such a multi-location-hovering solution, we present a successive hover-and-fly trajectory design and obtain the corresponding optimal transmit power allocation for the case with the maximum UAV speed constraint. Numerical results show that our proposed joint UAV trajectory and transmit power optimization significantly improves the achievable rate of the UAV-enabled multicast channel, and also greatly outperforms the conventional multicast channel with a fixed-location transmitter.Comment: To appear in the IEEE International Conference on Communications (ICC), 201

Channel Modeling and Characteristics for 6G Wireless Communications

[EN] Channel models are vital for theoretical analysis, performance evaluation, and system deployment of the communication systems between the transmitter and receivers. For sixth-generation (6G) wireless networks, channel modeling and characteristics analysis should combine different technologies and disciplines, such as high-mobil-ity, multiple mobilities, the uncertainty of motion trajectory, and the non-stationary nature of time/frequency/space domains. In this article, we begin with an overview of the salient characteristics in the modeling of 6G wireless channels. Then, we discuss the advancement of channel modeling and characteristics analysis for next-generation communication systems. Finally, we outline the research challenges of channel models and characteristics in 6G wireless communications.This research was supported by the National Key R&D Program of China under grant 2018YFB1801101; the National Nature Science Foundation of China (No. 61771248 and 61971167); the Jiangsu Province Research Scheme of Nature Science for Higher Education Institution (No. 14KJA510001); and the Open Research Fund of the National Mobile Communications Research Laboratory, Southeast University (No. 2020D14).Jiang, H.; Mukherjee, M.; Zhou, J.; Lloret, J. (2021). Channel Modeling and Characteristics for 6G Wireless Communications. IEEE Network. 35(1):296-303. https://doi.org/10.1109/MNET.011.200034829630335

Development and Validation of an IMU/GPS/Galileo Integration Navigation System for UAV

Several and distinct Unmanned Aircraft Vehicle (UAV) applications are emerging, demanding steps to be taken in order to allow those platforms to operate in an un-segregated airspace. The key risk component, hindering the widespread integration of UAV in an un-segregated airspace, is the autonomous component: the need for a high level of autonomy in the UAV that guarantees a safe and secure integration in an un-segregated airspace. At this point, the UAV accurate state estimation plays a fundamental role for autonomous UAV, being one of the main responsibilities of the onboard autopilot. Given the 21st century global economic paradigm, academic projects based on inexpensive UAV platforms but on expensive commercial autopilots start to become a non-economic solution. Consequently, there is a pressing need to overcome this problem through, on one hand, the development of navigation systems using the high availability of low cost, low power consumption, and small size navigation sensors offered in the market, and, on the other hand, using Global Navigation Satellite Systems Software Receivers (GNSS SR). Since the performance that is required for several applications in order to allow UAV to fly in an un-segregated airspace is not yet defined, for most UAV academic applications, the navigation system accuracy required should be at least the same as the one provided by the available commercial autopilots. This research focuses on the investigation of the performance of an integrated navigation system composed by a low performance inertial measurement unit (IMU) and a GNSS SR. A strapdown mechanization algorithm, to transform raw inertial data into navigation solution, was developed, implemented and evaluated. To fuse the data provided by the strapdown algorithm with the one provided by the GNSS SR, an Extended Kalman Filter (EKF) was implemented in loose coupled closed-loop architecture, and then evaluated. Moreover, in order to improve the performance of the IMU raw data, the Allan variance and denoise techniques were considered for both studying the IMU error model and improving inertial sensors raw measurements. In order to carry out the study, a starting question was made and then, based on it, eight questions were derived. These eight secondary questions led to five hypotheses, which have been successfully tested along the thesis. This research provides a deliverable to the Project of Research and Technologies on Unmanned Air Vehicles (PITVANT) Group, consisting of a well-documented UAV Development and Validation of an IMU/GPS/Galileo Integration Navigation System for UAV II navigation algorithm, an implemented and evaluated navigation algorithm in the MatLab environment, and Allan variance and denoising algorithms to improve inertial raw data, enabling its full implementation in the existent Portuguese Air Force Academy (PAFA) UAV. The derivable provided by this thesis is the answer to the main research question, in such a way that it implements a step by step procedure on how the Strapdown IMU (SIMU)/GNSS SR should be developed and implemented in order to replace the commercial autopilot. The developed integrated SIMU/GNSS SR solution evaluated, in post-processing mode, through van-test scenario, using real data signals, at the Galileo Test and Development Environment (GATE) test area in Berchtesgaden, Germany, when confronted with the solution provided by the commercial autopilot, proved to be of better quality. Although no centimetre-level of accuracy was obtained for the position and velocity, the results confirm that the integration strategy outperforms the Piccolo system performance, being this the ultimate goal of this research work

A Novel 3D Analytical Scattering Model for Air-to-Ground Fading Channels

A geometry-based three-dimensional (3D) novel stochastic channel model for air-to-ground (A2G) and ground-to-air (G2A) radio propagation environments is proposed. The vicinity of a ground station (GS) is modelled as surrounded by effective scattering points; whereas the elevated air station’s (AS) vicinity is modelled as a scattering-free region. Characterization of the Doppler spectrum, dispersion in the angular domain and second order fading statistics of the A2G/G2A radio communication channels is presented. Closed-form analytical expressions for joint and marginal probability density functions (PDFs) of Doppler shift, power and angle of arrival (AoA) are derived. Next, the paper presents a comprehensive analysis on the characteristics of angular spread on the basis of shape factors (SFs) for A2G/G2A radio propagation environments independently in both the azimuth and elevation planes. The analysis is further extended to second order statistics of the fading channel; where the behaviour of the level crossing rate (LCR), average fade duration (AFD), auto-covariance and coherence distance for the A2G/G2A radio propagation environment is studied. Finally, the impact of physical channel parameters, such as the mobility of AS, the height of AS, the height of GS and the delay of the longest propagation path, on the distribution characteristics of Doppler shift, angular spread and second order statistics is thoroughly studied

Low Frequency Radio Polarization Sensor with Applications in Attitude Estimation

A novel method of attitude (orientation) estimation is proposed, which makes use of measurements of the polarization of the magnetic (H-) field of Low Frequency (LF) radio signals. This offers advantages relative to existing accelerometer-based systems in high-acceleration, cost-constrained environments such as small fixed-wing Unmanned Aerial Vehicles. In order to validate this method, a sensor system is presented which is capable of determining the H-field polarization of LF radio signals from three-axis measurements. The sensor system consists of an array of three orthogonal loop antennas, a three channel radio receiver circuit, a datalogging and control module and data processing algorithms. This system is shown to accurately measure the axis of H-field polarization for signals with linear or almost linear polarization, subject to a sign ambiguity. A representative AM radio broadcast in the LF band is shown to have a substantially linear polarization, measurements of which are used to determine a receiver’s heading angle. The stability of these polarization measurements over time, and the distorting effect of certain structures, are quantified. The feasibility of this method of attitude determination is therefore demonstrated.This is the accepted manuscript of the article "Maguire, Sean; Robertson, Paul. "Low Frequency Radio Polarization Sensor with Applications in Attitude Estimation". IEEE Sensors Journal (Volume:PP , Issue: 99). 19 August 2015 . http://dx.doi.org/10.1109/JSEN.2015.2469679". (c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works

UAVs for the Environmental Sciences

This book gives an overview of the usage of UAVs in environmental sciences covering technical basics, data acquisition with different sensors, data processing schemes and illustrating various examples of application