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。     

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。     

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 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.     

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。     

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.     

Relay selection based on MAP estimation for cooperative communication with outdated channel state information

In this paper, we consider an amplify-and-forward (AF) cooperative communication system when the channel state information (CSI) used in relay selection differs from that during data transmission, i.e., the CSI used in relay selection is outdated. The selected relay may not be actually the best for data transmission and the outage performance of the cooperative system will deteriorate. To improve its performance, we propose a relay selection strategy based on maximum a posteriori (MAP) estimation, where relay is selected based on predicted signal-to-noise ratio (SNR). To reduce the computation complexity, we approximate the a posteriori probability density of SNR and obtain a closed-form predicted SNR, and a relay selection strategy based on the approximate MAP estimation (RS-AMAP) is proposed. The simulation results show that this approximation leads to trivial performance loss from the perspective of outage probability. Compared with relay selection strategies given in the literature, the outage probability is reduced largely through RS-AMAP for medium-to-large transmitting powers and medium-to-high channel correlation coefficients.     

固定翼无人机编队集结控制算法研究

针对固定翼无人机协同作战时的编队集结问题，提出了一种新的路径规划和位置分配方法，并设计了包括航迹跟踪、高度保持和速度控制在内的自动驾驶仪。该路径规划算法通过矩阵迭代得到一组较优的目标点分配方案，满足总航程较小和同时到达约束。根据得到的各无人机飞向目标点的航迹，算出无人机编队集结的代价矩阵。在每架无人机确定了应飞航路后，开始沿航路飞向目标点，在此过程中，纵向采用高度保持自动驾驶仪，横向采用航迹跟踪自动驾驶仪，控制无人机按规定航迹飞行。速度调节自动驾驶仪可根据速度指令调节油门大小加减速，跟踪上目标速度，进而实现编队集结。仿真结果验证了所提出的编队集结控制方法的有效性和可行性。     

基于罚函数序列凸规划的多无人机轨迹规划

多无人机（UAVs）轨迹规划是具有非线性运动约束和非凸路径约束的最优控制问题。引入序列凸规划思想,将非凸最优控制问题近似为一系列凸优化子问题,并利用成熟的凸优化算法进行求解,以更好地权衡最优性和时效性。首先,建立了多无人机协同轨迹规划的非凸最优控制模型。然后,利用离散化和凸近似方法将其转换为凸优化问题,包括对无人机运动模型的线性化,以及对威胁规避约束和无人机碰撞约束的凸化。同时,提出了一种离散点间的威胁规避方法,保证无人机在离散轨迹点间的飞行安全。在凸优化模型的基础上,给出了基于罚函数序列凸规划求解多无人机轨迹规划的具体框架。最后,通过数值仿真验证了方法的有效性,结果表明该方法在多机轨迹规划结果的最优性和时效性都要优于伪谱法,而且优势随编队数量的增加而增大。     

基于改进A^*算法的无人机快速轨迹规划方法

针对旋翼无人机在三维障碍物环境中自主飞行时路径搜索速度慢、轨迹生成通常忽略无人机动力学特性的问题,发展一种基于改进A^*算法并同时考虑无人机动力学特性和运动学性能的快速轨迹规划方法。首先,在三维障碍物环境中运用改进A^*算法通过剔除部分网格节点降低A^*算法的节点计算量,提升算法的路径搜索速度;其次,以最小化飞行轨迹的四阶导数作为目标函数,以路径点处的位置、速度、加速度等各阶导数作为约束条件优化飞行轨迹;最后,在三维障碍物环境中对比A^*算法改进前后的路径搜索结果,并对优化的飞行轨迹进行仿真飞行测试。结果表明:改进A^*算法大幅降低了A^*算法的节点计算量,显著提升了路径搜索速度;且无人机能够始终以较小位置误差沿优化轨迹光滑连续飞行。     

基于Proximal-Newton-Kantorovich凸规划的空天飞行器实时轨迹优化

针对空天飞行器大气层内上升段实时轨迹优化问题，提出一种基于Proximal-Newton-Kantorovich凸规划的轨迹优化方法。首先，应用Newton-Kantorovich迭代方法将轨迹优化问题转化为一系列的子问题，每个子问题都是一个线性最优控制问题；其次，针对Newton-Kantorovich迭代方法忽略运动方程中的高阶信息，导致难以收敛这一问题，提出Proximal-Newton-Kantorovich迭代方法，在子问题的性能指标中加入邻近规则化项，改善了Newton-Kantorovich迭代方法的收敛性；最后，将子问题离散为二阶锥规划问题，并应用内点法进行求解。提出的Proximal-Newton-Kantorovich凸规划方法是一种求解非线性轨迹规划问题的可行途径。理论分析表明，Proximal-Newton-Kantorovich迭代方法的收敛结果一定是轨迹优化问题的局部最优解。数值实验表明，此方法的计算时间在毫秒级。     

应用轨迹优化策略的直升机任务科目基元仿真

任务科目基元的飞行试验是ADS-33E-PRF对直升机飞行品质的判定标准。针对直升机设计过程中飞行品质难以事先评定的特点,提出了一种基于轨迹优化策略的直升机任务科目基元数值仿真方法。该方法将飞行品质规范对直升机位置、姿态和速度的限制处理为状态量的边界约束,以完成任务科目基元的时间为目标函数,结合直升机自身的性能和安全性约束,建立了针对任务科目基元的直升机轨迹优化模型。求解该模型得到直升机完成相应任务科目基元所用的时间,便可定性判断直升机飞行品质是否满足ADS-33E-PRF对这一任务科目基元的要求,从而在设计之初对优化直升机总体设计参数提供参考。对某型直升机悬停转弯机动科目进行仿真计算,验证了该方法的正确性和有效性。     

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...     

Optimal trajectory and downlink power control for multi-type UAV aerial base stations

Unmanned Aerial Vehicles (UAVs) enabled Aerial Base Stations (UABSs) have been studied widely in future communications. However, there are a series of challenges such as interference management, trajectory design and resource allocation in the scenarios of multi-UAV networks. Besides, different performances among UABSs increase complexity and bring many challenges. In this paper, the joint downlink transmission power control and trajectory design problem in multi-type UABSs communication network is investigated. In order to satisfy the signal to interference plus noise power ratio of users, each UABS needs to adjust its position and transmission power. Based on the interactions among multiple communication links, a non-cooperative Mean-Field-Type Game (MFTG) is proposed to model the joint optimization problem. Then, a Nash equilibrium solution is solved by two steps: first, the users in the given area are clustered to get the initial deployment of the UABSs; second, the Mean-Field Q (MFQ)-learning algorithm is proposed to solve the discrete MFTG problem. Finally, the effectiveness of the approach is verified through the simulations, which simplifies the solution process and effectively reduces the energy consumption of each UABS.     

一种基于QoS的自适应混合协同传输方法及性能分析

理想的混合协同传输系统中,所有的中继节点都参与译码,将带来计算复杂度的提高、节点资源消耗的增加以及信息传输时延的增大。针对多节点的协同无线传输网络,提出了一种基于服务质量(Quality of Service, QoS)的自适应混合协同传输方法,并进行了性能分析,给出了系统误码率(Symbol Error Rate, SER)及中断概率的闭合表达式。该方法根据目的节点的QoS需求以及中继节点的信噪比(SNR)门限,动态地调整中继节点的传输模式,能够减小系统能耗,延长节点使用寿命。数值及仿真结果表明,基于中继节点信噪比门限的混合协同传输能够以较低的实现复杂度获得与理想的混合协同传输相近的性能,理论的性能分析结果与实际仿真结果相一致。     

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.     

样条节点优化方法及其在弹道表示中的应用

精确的主动段弹道表示模型是高精度弹道参数估计算法的关键。针对等距节点样条模型表示主动段弹道截断误差过大问题,引入一种基于残差的自适应样条节点优化方法,用自由节点样条表示主动段弹道,并根据假设检验理论给出算法中的阈值确定方法。仿真结果表明,经该方法进行节点优化后的样条模型,不但能有效控制模型误差,当检验水平较高时,还能初步识别导弹主动段特征点。     

无人机编队支撑网络的协同通信中继策略

针对无人机编队支撑网络优化选择中继成员进而提高编队协同通信能力问题，基于端到端技术（Device-to-Device，D2D），提出了一种同时考虑无人机编队成员的邻近域及编队成员间的社会性依存关系来优化选择中继成员的中继策略，旨在既能保证无人机编队的基本通信能力，又能同时优化提高编队的吞吐量，从而进一步提升编队支撑网络的整体性能。研究结果表明，所提的无人机编队支撑网络中继成员优化选择策略在系统吞吐量方面较已有方法具有明显优势。     

考虑多边界状态约束的飞翼布局无人机姿态控制

以大展弦比飞翼布局无人机为研究对象,针对强扰动环境下多边界状态约束时的飞行姿态控制问题,提出一种指令-控制律联合限制的全状态约束控制方法。该控制方法分别独立设计了指令边界限制器、过渡指令产生器和指令跟踪控制器3个部分。首先,基于无人机动力学特性设计的指令边界限制器,利用无人机的各个状态边界来限制姿态控制器的指令,实现了将非受控状态的约束问题转化为受控状态的约束问题;其次,基于"安排过渡过程"的思想并考虑约束限制环节,设计了过渡指令产生器,为无人机在线生成从当前姿态到期望跟踪姿态的过渡指令;最后,基于障碍Lyapunov函数和扩张状态观测器,设计了指令跟踪控制器,使无人机能够克服干扰且快速稳定地跟踪过渡指令。通过采用Lyapunov稳定性理论分析,该控制方法能够保证姿态跟踪误差收敛有界,且始终处于给定区间内部。仿真结果表明,该控制方法能够保证无人机飞行状态在不超出约束边界的同时,实现对姿态指令的准确跟踪。     

Timeliness optimization of unmanned aerial vehicle lossy communications for internet-of-things

Information freshness is a key factor for Internet-of-Things(Io T) to make appropriate decisions and operations. This paper proposes an analytical framework for evaluating the timeliness performance of the Io T system based on Unmanned Aerial Vehicle(UAV) lossy communications.The performance analysis consists of the outage probability analysis and the Age-of-Information(Ao I) analysis with outages. To begin with, we solve a lossy coding problem formulated from the UAV communication system, and d...