Energy-efficiency maximization for fixed-wing UAV-enabled relay network with circular trajectory

With the development of Unmanned Aerial Vehicles (UAVs), the applications of UAVs have been extensively explored. In the field of wireless communications, the relay nodes are often used to extend network coverage. However, traditional fixed ground relays cannot be flexibly deployed due to their low heights and fixed locations. Hence, deploying UAV as relay node is a promising solution and has become a research hotspot. In this paper, we consider an UAV-enabled relaying network in which a fixed-wing UAV is deployed between the Base Station (BS) and Ground Users (GUs). We study the energy-efficiency gap between the link “BS-UAV-GUs” and the link “BS-GUs”, and jointly optimize UAV relay transmission power and flight radius to achieve the highest energy-efficiency. Firstly, the UAV/BS-GUs channels models and the UAV energy consumption model are built. Secondly, the optimization objective function is formulated to maximize the energy-efficiency gap. Then, the solution of the optimization problem is divided into a two-step iteration process, in which the UAV relay transmission power and flight radius are adjusted to maximize the energy-efficiency gap. Finally, the experimental results under different simulation scenarios (such as cities, forests, deserts, oceans, etc.) are shown to illustrate the effectiveness of the proposed algorithm. The results show that the proposed algorithm can always find the optimal UAV relay transmission power and flight radius settings, and achieve the largest energy-efficiency gap. The convergency speed of the proposed algorithm is fast, and can obtain the optimal solution within only a few iterations.     

Optimization of beamforming and path planning for UAV-assisted wireless relay networks

Recently, unmanned aerial vehicles （UAVs） acting as relay platforms have attracted considerable attention due to the advantages of extending coverage and improving connectivity for long-range communications. Specifically, in the scenario where the access point （AP） is mobile, a UAV needs to find an efficient path to guarantee the connectivity of the relay link. Motivated by this fact, this paper proposes an optimal design for beamforming （BF） and UAV path planning. First of all, we study a dual-hop amplify-and-forward （AF） wireless relay network, in which a UAV is used as relay between a mobile AP and a fixed base station （BS）. In the network, both of the AP and the BS are equipped with multiple antennas, whereas the UAV has a single antenna. Then, we obtain the output signal~to-noise ratio （SNR） of the dual-hop relay network. Based on the criterion of maximizing the output SNR, we develop an optimal design to obtain the solution of the optimal BF weight vector and the UAV heading angle. Next, we derive the closed-form outage probability （OP） expression to investigate the performance of the dual-hop relay network conveniently. Finally, computer simulations show that the proposed approach can obtain nearly optimal flying path and OP performance, indicating the effectiveness of the proposed algorithm. Furthermore, we find that increasing the antenna number at the BS or the maximal heading angle can significantly improve the performance of the considered relay network.     

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。     

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。     

毫米波通信定位一体化自组网资源分配技术

毫米波通信链路具有低延迟、高速率和高定向性的特点,能够实现高速率自组网通信和高精度节点定位。在通信定位一体化背景下,研究了毫米波自组网中的多用户资源分配问题。系统采用基于正交频分多址(OFDMA)的多用户通信定位一体化框架,推导了基于位置估计误差界(PEB)和方位估计误差界(OEB)的多用户定位性能准则和基于数据速率的通信准则,建立了时域和频域的资源分配优化问题模型,在保障链路通信速率的前提下,最优化用户的定位性能指标。为了求解上述混合整数非线性规划问题,引入广义Benders分解算法,将优化问题分解为主问题和子问题进行迭代求解,得到有效的资源分配结果,最后通过仿真验证了资源分配对定位与通信性能的影响以及算法的有效性。     

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(Lo S)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 jamm...     

非对称衰落信道下无人机中继传输方案及性能分析

 无人机(UAV)作为中继传输平台受到了国内外研究人员的广泛关注。本文研究了非对称衰落信道下的无人机中继传输系统,提出了输出信噪比最大化准则下的波束形成(BF)优化方案,并推导出系统中断概率、遍历容量和平均误符号率等无线通信系统主要性能指标的理论表达式。通过计算机仿真验证了本文提出的中继传输方案及性能分析的正确性,并定量分析了天线数量、信道参数以及功率分配对系统性能的影响,为无人机中继传输系统的设计及性能评估提供了参考和依据。     

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.     

基于多机协作的认知无人机网络能效联合优化

针对无人机（UAV）通信网络中频谱资源紧缺的问题,构建基于认知无线电的多无人机通信网络,通过多机协作频谱感知有效探索授权频谱。提出一种基于Bisection算法的迭代算法,通过联合优化感知时间和判决门限对构建的复杂非凸问题求解,显著提高了无人机次级认知网络的能量效率（EE）。分析了无人机飞行过程中能效的变化情况,仿真结果表明,存在最优感知时间使能效获得最大值,且判决门限的选择会影响该能效最优值;提出的高能效迭代算法具有较好收敛性,有效提高了认知无人机网络的能量利用率。     

Mobility control of unmanned aerial vehicle as communication relay in airborne multi-user systems

In this paper, a model-based adaptive mobility control method for an Unmanned Aerial Vehicle(UAV) acting as a communication relay is presented, which is intended to improve the network performance in airborne multi-user systems. The mobility control problem is addressed by jointly considering unknown Radio Frequency(RF) channel parameters, unknown multi-user mobility, and non-available Angle of Arrival(AoA) information of the received signal. A Kalman filter and a least-square-based estimation algorithm are used to predict the future user positions and estimate the RF channel parameters between the users and the UAV, respectively. Two different relay application cases are considered: end-to-end and multi-user communications. A line search algorithm is proposed for the former, with its stability given and proven, whereas a simplified gradient-based algorithm is proposed for the latter to provide a target relay position at each decision time step, decreasing the two-dimensional search to a one-dimensional search. Simulation results show that the proposed mobility control algorithms can drive the UAV to reach or track the optimal relay position movement, as well as improving network performance. The proposed method reflects the properties of using different metrics as objective network performance functions.     

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.     

多植保无人机协同路径规划

为实现多植保无人机（UAVs）协同作业，并提高作业效率，提出了一种基于改进粒子群优化（PSO）的多植保无人机协同路径规划算法。根据作业区域的形状面积和植保UAV的作业参数划分各架UAV作业区域，采用栅格法生成各区域全覆盖作业航线。以各架植保UAV各架次植保作业距离为算法寻优变量，在确保各架UAV补给时间满足间隔分布约束条件下，综合考虑补给总次数、返航补给总时间、总耗时和最小补给时间间隔4项因素，并构成目标函数，通过采用改进PSO算法，实现了对各UAV返航顺序和返航点位置的寻优。仿真分析结果表明，相较于最大作业距离规划和最小返航距离规划，本文提出的规划算法表现出了较优的性能和较好的作业区域适应性，证实了其有效性和实用性。     

无人机系统的卫星中继数据链

针对大中型无人机系统实现远程测控与信息传输的技术需求,在参考国外＂捕食者＂、＂全球鹰＂等先进无人机系统技术体制和实现方案的基础上,提出了利用商业或军用通信卫星作为空中中继平台,建立无人机卫星中继数据链,实现我国远程无人机系统的超视距遥控、遥测和侦察信息实时传输的解决方案,这对延伸无人机系统的作用距离、提高作战效能具有重要意义。文中分析了无人机系统卫星中继数据链的技术体制,提出了工程应用中的关键技术,对具体的工程实现具有一定的指导意义。     

低成本多传感器组合导航系统在小型无人机自主飞行中的研究与应用

为了满足小型无人机自主控制系统对导航系统性能的要求,研究低成本的基于微机电系统的捷联惯性导航系统(MEMS-SINS)/全球定位系统(GPS)/磁强计组合导航系统。提出一种利用磁强计辅助MEMS-SINS的静基座初始姿态确定方法,采用四元数误差模型对MEMS-SINS/GPS/磁强计组合导航系统进行信息融合的建模,采用基于正交三角(QR)分解的平方根无色卡尔曼滤波(UKF)非线性估计方法对组合导航系统进行数据融合,克服由于计算机舍入误差引起的状态协方差阵的计算值失去非负定性甚至对称性,通过小型无人机的自主飞行试验,证实MEMS-SINS/GPS/磁强计组合导航算法满足小型无人机自主控制系统的要求。     

导航辅助下基于LAS码的天基多目标测控

中继卫星的天基测控是解决中低轨道航天器大范围、长时间、多目标测控的有效途径,但用户星到中继卫星的时延误差、多普勒频移校正误差等参数会对多目标测控带来干扰。针对该问题,首先分析了定位误差引起的时延误差、多普勒频移校正误差等因素,设计了天基多目标前向链路遥控SMA(S-band Multiple Access,S频段多址)信号形式和反向遥测链路SMA信号形式,选择与时延校正误差相匹配的LAS(Large Area Synchronous,大区域同步)码作为反向遥测信息的扩频码,建立了导航辅助的终端时延和频率预校正方案模型,可以有效消除多用户干扰。仿真表明,当Eb/N0≥10.5dB时,前向遥控信息误码率pe≤1×10~(-6),反向遥测信息误码率pe≤1×10~(-6),使用LAS码比Gold序列约有2dB性能改善,为基于我国天链卫星的中低轨道卫星稳定运行、载人航天交会对接以及后续空间站建设等任务的测控提供重要参考。     

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.     

下一代数据中继卫星系统发展思考

通过系统阐述中继卫星系统的发展过程,给出了主要国家和组织的中继卫星系统技术体制和现状.再结合卫星、载人航天器和深空探索的未来发展趋势,分析了下一代中继卫星系统的发展需求.在此基础上,从体系结构、卫星平台、链路调制体制、网络协议等方面,探讨并给出了下一代中继卫星系统的发展趋势和技术途径.为满足未来近地、深空航天任务,以及临近、低空快速移动用户的不同要求,节约系统成本,下一代中继卫星系统将向专业化和与其他系统融合的方向发展:星间链路将增加激光链路,数据速率可达到10 Gbit/s以上;多址业务成为主用,同时支持用户数能力将极大提高;对于链路调制体制,在采用CR(Cognitive Radio,认知无线电)和SDR(Software Defined Radio,软件定义无线电)技术的基础上,可实现实时自适应调整和根据需求加载配置;数据传输将采用网络化方式,天地间构成一体化DTN(Delay Tolerant Network,容延迟网络).     

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.     

基于中继测量的环月探测器定轨能力分析

嫦娥四号月球探测拟首次实现月球背面的软着陆,测控与数传依赖地月L2平动点的中继卫星,并有望获取四程测量与星间测量数据。对基于中继测量的环月探测器测定轨能力进行了仿真分析,结果表明,中继卫星可较好地实现环月探测器连续跟踪;在定轨能力方面,中继卫星自身轨道精度是制约环月探测器定轨精度的重要因素,当跟踪弧段达到5h以上时,定轨精度趋于稳定,但轨道精度较中继卫星的轨道精度相差1个量级;对于星间链路测量,除中继卫星自身的轨道精度外,星钟的稳定性是制约定轨精度的另一个重要因素,如果辅助以每天1h的地基跟踪亦可实现优于百m的定轨精度。     

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.