Proactive optimization of transmission power and 3D trajectory in UAV-assisted relay systems with mobile ground users

In this paper, an Unmanned Aerial Vehicle (UAV)-assisted relay communication system is studied, where a UAV is served as a flying relay to maintain a communication link between a mobile source node and a remote destination node. Specifically, an average outage probability minimization problem is formulated firstly, with the constraints on the transmission power of the source node, the maximum energy consumption budget, the transmission power, the speed and acceleration of the flying UAV relay. Next, the closed-form of outage probability is derived, under the hybrid line-of-sight and non-line-of-sight probability channel model. To deal with the formulated nonconvex optimization, a long-term proactive optimization mechanism is developed. In particular, firstly, an approximation for line-of-sight probability and a reformulation of the primal problem are given, respectively. Then, the reformulated problem is transformed into two subproblems: one is the transmission power optimization with given UAV’s trajectory and the other is the trajectory optimization with given transmission power allocation. Next, two subproblems are tackled via tailoring primal–dual subgradient method and successive convex approximation, respectively. Furthermore, a proactive optimization algorithm is proposed to jointly optimize the transmission power allocation and the three-dimensional trajectory. Finally, simulation results demonstrate the performance of the proposed algorithm under various parameter configurations.     

Ergodic sum rate for uplink NOMA transmission in satellite-aerial-ground integrated networks

The application of Non-Orthogonal Multiple Access (NOMA) technology into satellite-aerial-ground integrated networks can meet the requirements of ultra-high rate and massive connectivity for the Sixth-Generation (6G) communication systems. We consider an uplink NOMA scenario for such a satellite-aerial-ground integrated network where multiple users communicate with satellite under the help of an Unmanned Aerial Vehicle (UAV) as an aerial relay equipped with a phased array. Supposing that buffer-aided decode-and-forward protocol is adopted at the UAV relay, we first formulate an optimization problem to maximize Ergodic Sum Rate (ESR) of the considered system subject to individual power constraint and quality-of-service constraint of each user. Then, with known imperfect channel state information of each user, we propose a joint power allocation and robust Beam Forming (BF) iterative algorithm to maximize ESR for the user-to-UAV link. Besides, to take the advantages of Free-Space Optical (FSO) and millimeter Wave (mmWave) communications, we present a switch-based hybrid FSO/mmWave scheme and a robust BF algorithm for the UAV-to-satellite link to achieve higher rate. Moreover, a closed-form ESR expression is derived. Finally, the effectiveness and correctness of the proposed solutions are verified by numerical simulations, and the performance evaluation results show that the proposed solutions not only achieve performance enhancement and robustness, but also outperform the orthogonal multiple access significantly.     

Robust trajectory planning for UAV communication systems in the presence of jammers

Unmanned Aerial Vehicle (UAV) has emerged as a promising novel application for the Sixth-Generation (6G) wireless communication by leveraging more favorable Line-of-Sight (LoS) propagation. However, the jamming resistance by exploiting UAV’s mobility is a new challenge in the UAV-ground communication. This paper investigates the trajectory planning problem in an UAV communication system, where the UAV is operated by a Ground Control Unit (GCU) to perform certain tasks in the presence of multiple jammers with imperfect power and location information. To ensure the reliability of the GCU-to-UAV link, we formulate the problem as a non-convex semi-infinite optimization, aiming to maximize the average worst-case Signal-to-Interference-plus-Noise Ratio (SINR) over a given flight duration by designing the robust trajectory of the UAV under stringent energy availability constraints. To handle this problem efficiently, we develop an iterative algorithm for the solution with the aid of S-procedure and Successive Convex Approximation (SCA) method. Numerous results demonstrate the efficacy of our proposed algorithm and offer some useful design insights to practical system.     

空时分组编码的无人机中继通信航迹规划方法

无人机(UAV)中继通信是实现远距离点对点无线通信的一种重要技术手段。为提高无人机中继通信系统链路传输的可靠性,提出基于空时分组编码的无人机放大转发中继通信传输方案,并基于双跳链路遍历容量最大化的准则给出了无人机最佳航迹规划方法,并进一步利用FM-EM算法给出了基于空时分组编码无人机中继通信系统的中断概率及遍历信道容量计算公式。计算机仿真表明:提出的方法显著优于传统的单发单收(SISO)无人机中继通信系统。     

Distortion minimization for multimedia transmission in NOMA HAP-UAV integrated aerial access networks

Aerial access networks have been envisioned as a promising 6G solution to enhance the ground communication systems in both coverage and capacity. To better utilize the spectrum and fully explore different channel characteristics, this paper constructs an integrated network comprising the High Altitude Platform (HAP) and Unmanned Air Vehicles (UAVs) with the Non-Orthogonal Multiple Access (NOMA) technology. In order to improve the transmission quality of images and videos, a power management scheme is proposed to minimize the distortion of the transmissions from the HAP and UAVs to the terminals. The power control is formulated as a non-convex problem constrained by the maximal transmit power and the minimal terminal rate requirements. The variable substitution and the first-order Tailor’s expansion is used to transform it into a sequence of convex problems, which are subsequently solved through the gradient projection method. Simulation demonstrates the signal distortion and error rate improvement achieved by the proposed algorithm.     

一种方向舵-螺旋桨联用的全翼式太阳能无人机横航向控制方法

以全翼式太阳能无人机（UAV）为研究对象,针对无副翼状态下横航向控制问题,提出了采用方向舵偏转和螺旋桨差动进行横航向控制的方法。首先,分析了两个螺旋桨条件下该类无人机横航向的稳定性与操纵性;然后,基于线性自抗扰控制（LADRC）理论,以方向舵偏和螺旋桨差动为控制输出,分别设计了滚转角控制器和偏航角控制器。最后,结合滚转角控制和偏航角控制的优缺点,在L1轨迹跟踪算法的基础上设计了方向舵和螺旋桨联用的直线轨迹跟踪器。仿真结果表明：所设计的控制器具有较好的控制性能、鲁棒性和抗风性。同时参数整定过程相对简单,并采用实际可测的物理量,为进一步工程应用提供参考。     

Energy-efficient data collection for UAV-assisted IoT: Joint trajectory and resource optimization

Internet of Things (IoT) can be conveniently deployed while empowering various applications, where the IoT nodes can form clusters to finish certain missions collectively. As energy-efficient operations are critical to prolong the lifetime of the energy-constrained IoT devices, the Unmanned Aerial Vehicle (UAV) can be dispatched to geographically approach the IoT clusters towards energy-efficient IoT transmissions. This paper intends to maximize the system energy efficiency by considering both the IoT transmission energy and UAV propulsion energy, where the UAV trajectory and IoT communication resources are jointly optimized. By applying large-system analysis and Dinkelbach method, the original fractional optimization is approximated and reformulated in the form of subtraction, and further a block coordinate descent framework is employed to update the UAV trajectory and IoT communication resources iteratively. Extensive simulation results are provided to corroborate the effectiveness of the proposed method.     

Battery package design optimization for small electric aircraft

The increasing gross weight of electric Unmanned Aerial Vehicle (UAV) poses a challenge in practical applications. The range and endurance of the electric UAV are limited by the fixed mass of the battery package. In this work, a design optimization method for the battery package topology of small electric UAV is proposed to enhance the performance. To improve the accuracy of the method, the dynamic battery model and simplified electric component models are presented. These models are utilized by the trajectory optimization method, which takes the dynamic characteristic into consideration to calculate the aircraft performance. The direct optimal control method is used for solving the trajectory optimization problem, and this method is tested on a small blended-wing-body electric aircraft. The test result shows that the range and energy-consumption are mainly influenced by the parallel topology of the battery package, while the flight time in climb phase is more sensitive to the series topology. It is deduced that the range- and energy-optimal design points can be considered concurrently in design optimization. The work proves the feasibility of integrating the trajectory optimization and battery package design.     

Optimal video communication strategy for intelligent video analysis in unmanned aerial vehicle applications

For Unmanned Aerial Vehicles (UAV), the intelligent video analysis is a key technology in intelligent autonomous control, real-time navigation and surveillance. However, poor UAV wireless links would degrade the quality of video communication, leading to difficulties in video analysis. To meet the challenges of packet-loss and limited bandwidth in adverse UAV channel environments, this paper proposes a parameter optimization mechanism for UAV intelligent video analysis. In the proposed method, an Optimal Strategy Library (OSL) is designed to optimize the parameters for video encoding and forward error correction. Adapted to the packet-loss rate and bandwidth in practical UAV wireless network, the proposed OSL can facilitate the encoding of video sequences and the recovery of degraded videos with optimal performance. Experimental results demonstrate that the proposed solution can keep intelligent video analysis working efficiently with adverse UAV wireless links, and is capable of maximizing the inference accuracy of Multi-Object Tracking (MOT) algorithms in various scenarios.     

认知无线电网络中基于几何规划的分布式功率控制

功率控制对于允许次用户和主用户之间频谱共享的认知无线电网络来说是关键的,针对具有干扰限制的认知网络最大总容量得到一种最优的分步式功率控制策略,对于系统效用的非凸性,引入几何规划把非凸最优化问题转换为凸最优化问题,引入辅助变量和额外等式约束,把效用之间的关联转化为约束之间的关联,提出了功率控制策略的解决方法,显示了整体最...     

超长航时太阳能无人机关键技术综述

超长航时太阳能无人机（UAV）以其高效节能、原理上可实现无限巡航的特点受到广泛关注，而其独特的设计指标与任务特性也对各项关键技术提出了较高要求。多设计要素的高度耦合意味着不同于常规飞行器的总体设计方法，低密度、低速度的飞行条件使其具有明显的低雷诺数气动特性，柔性超大展弦比机翼带来了复杂的气动弹性问题，低翼载荷特性与较大的风场扰动增加了控制难度，极端的飞行环境与苛刻的任务指标对能源、动力系统带来了新挑战，飞行性能对能源系统的高度依赖开辟了飞行轨迹优化的研究方向。本文梳理了超长航时太阳能无人机关键技术的研究现状，在此基础上对各项技术中的难点问题进行了阐释，并对超长航时太阳能无人机未来发展趋势进行了展望。     

基于分解策略的SSO发射轨道遗传全局优化设计

提出了基于轨道分解优化和遗传算法（GA）的SSO发射轨道优化设计策略。针对多个轨道段相互耦合问题,基于分解优化策略,将整个发射轨道设计问题分解为两个轨道段设计问题。为了高效可靠地获得全局最优解,对基本遗传算法进行了改进。首先提出了基于多变异操作等改进措施的改进遗传算法;此外,结合遗传算法的全局搜索特性和Powell算法的局部搜索特性,设计了一种串行混合遗传算法。一个二级SSO运载火箭的计算结果表明,轨道分解优化策略确保了问题的成功求解,改进遗传算法和混合遗传算法均可稳定地获得全局最优解,但是混合算法更有效地提高了GA性能。     

Robust leaderless time-varying formation control for unmanned aerial vehicle swarm system with Lipschitz nonlinear dynamics and directed switching topologies

This paper tackles the robust leaderless Time-Varying Formation(TVF) control problem for the Unmanned Aerial Vehicle(UAV) swarm system with Lipschitz nonlinear dynamics, external disturbances and directed switching topologies. In comparison with the previous achievements on formation control problems, the UAV swarm system with Lipschitz nonlinear dynamics can accomplish the pre-designed TVF while tracking a pre-given trajectory which is produced by a virtual leader UAV in the presence of externa...     

A distributed approach for lidar-based relative state estimation of multi-UAV in GPS-denied environments

In this paper, we present a distributed framework for the lidar-based relative state estimator which achieves highly accurate, real-time trajectory estimation of multiple Unmanned Aerial Vehicles(UAVs) in GPS-denied environments. The system builds atop a factor graph, and only onboard sensors and computing power are utilized. Benefiting from the keyframe strategy, each UAV performs relative state estimation individually and broadcasts very partial information without exchanging raw data. The com...     

Green UAV communications for 6G: A survey

Unmanned Aerial Vehicles (UAVs) have received a wide range of attention for military and commercial applications. Enhanced with communication capability, UAVs are considered to play important roles in the Sixth Generation (6G) networks due to their low cost and flexible deployment. 6G is supposed to be an all-coverage network to provide ubiquitous connections for space, air, ground and underwater. UAVs are able to provide air-borne wireless coverage flexibly, serving as aerial base stations for ground users, as relays to connect isolated nodes, or as mobile users in cellular networks. However, the onboard energy of small UAVs is extremely limited. Thus, UAVs can be only deployed to establish wireless links temporarily. Prolonging the lifetime and developing green UAV communication with low power consumption becomes a critical challenge. In this article, a comprehensive survey on green UAV communications for 6G is carried out. Specifically, the typical UAVs and their energy consumption models are introduced. Then, the typical trends of green UAV communications are provided. In addition, the typical applications of UAVs and their green designs are discussed. Finally, several promising techniques and open research issues are also pointed out.     

Virtual target guidance-based distributed model predictive control for formation control of multiple UAVs

The paper proposes a Virtual Target Guidance (VTG)-based distributed Model Predictive Control (MPC) scheme for formation control of multiple Unmanned Aerial Vehicles (UAVs). First, a framework of distributed MPC scheme is designed in which each UAV only shares the information with its neighbors, and the obtained local Finite-Horizon Optimal Control Problem (FHOCP) can be solved by swarm intelligent optimization algorithm. Then, a VTG approach is developed and integrated into the distributed MPC scheme to achieve trajectory tracking and obstacle avoidance. Further, an event-triggered mechanism is proposed to reduce the computational burden for UAV formation control, which takes into consideration the predictive state errors as well as the convergence of cost function. Numerical simulations show that the proposed VTG-based distributed MPC scheme is more computationally efficient to achieve formation control of multiple UAVs in comparison with the traditional distributed MPC method.     

频率选择性衰落信道DS-CDMA无人机中继通信系统航迹规划

无人机中继通信是实现远距离无线通信的一种重要技术手段，无人机的飞行航迹对无人机中继通信系统的链路传输可靠性存在显著的影响，在频率选择性衰落信道环境下研究了基于直序列码分多址（DS-CDMA）的无人机中继通信系统的航迹优化的问题。首先，给出了基于DS-CDMA的译码转发无人机中继通信系统的模型，并理论分析给出无人机中继通信系统的链路中断概率及平均误码率计算公式，以此为基础，基于链路中断概率最小化准则提出了中继无人机的航迹规划方法，最后通过仿真验证了所提出方法的正确性与有效性。研究表明：最大比值合并DS-CDMA无人机中继通信系统可充分获取频率选择性衰落信道提供的分集增益，显著改善链路传输的可靠性。     

集群无人机队形重构及虚拟仿真验证

队形重构是集群无人机（UAV）控制的重要问题，指无人机按照要求安全、无碰撞地从一个队形变换到另一个队形，其难点在于快速规划最优安全轨迹并控制无人机进行轨迹姿态的高精度跟踪。针对集群无人机队形重构的上述问题，首先，基于CAPT（Concurrent Assignment and Planning of Trajectories）算法，解决了多无人机的目标分配和轨迹生成的实时性问题，实现了集群无人机的最优安全路径规划；其次，提出一种有限时间多变量积分滑模连续控制算法，解决了无人机轨迹姿态的高精度跟踪问题，并通过MATLAB仿真验证了该控制算法的有效性；最后，为了更加真实直观地演示无人机三维仿真效果，建立了基于Gazebo-ROS的无人机仿真平台，实现了12架四旋翼无人机队形重构"建模-仿真-可视化"的一体化仿真演示，验证了上述路径规划算法和轨迹姿态控制算法的有效性。     

Multi-UAV coordination control by chaotic grey wolf optimization based distributed MPC with event-triggered strategy

The paper proposes a new swarm intelligence-based distributed Model Predictive Control (MPC) approach for coordination control of multiple Unmanned Aerial Vehicles (UAVs). First, a distributed MPC framework is designed and each member only shares the information with neighbors. The Chaotic Grey Wolf Optimization (CGWO) method is developed on the basis of chaotic initialization and chaotic search to solve the local Finite Horizon Optimal Control Problem (FHOCP). Then, the distributed cost function is designed and integrated into each FHOCP to achieve multi-UAV formation control and trajectory tracking with no-fly zone constraint. Further, an event-triggered strategy is proposed to reduce the computational burden for the distributed MPC approach, which considers the predicted state errors and the convergence of cost function. Simulation results show that the CGWO-based distributed MPC approach is more computationally efficient to achieve multi-UAV coordination control than traditional method.     

Optimization of bits allocation and path planning with trajectory constraint in UAV-enabled mobile edge computing system

In this paper, an Unmanned Aerial Vehicle (UAV) enabled Mobile Edge Computing (MEC) system is studied, in which UAV acts as server to offer computing offloading service to the Mobile Users (MUs) with limited computing capability and energy budget. We aim to minimize the total energy consumption of MUs by jointly optimizing the bit allocation for uplink, computing at the UAV and downlink, along with the UAV trajectory in a unified framework. To this end, a trajectory constraint model is employed to avoid sudden changes of velocity and acceleration during flying. Due to high-order information in use, we lead to a more reasonable nonconvex optimization problem than prior arts. An Alternating Direction Method of Multipliers (ADMM) method is introduced to solve the optimization problem, which is decomposed into a set of easy sub-problems, to meet the requirement on the efficiency in edge computing. Numerical results demonstrate that our approach leads a smoother UAV trajectory, significantly save the energy consumption for UAV during flying.