航空自组网STDMA时隙分配算法的设计与实现

航空自组网(AANET)是一种节点高速运动、网络拓扑持续快速变化的新型自组织网络。针对AANET的特点,提出了一种新的时分多址(TDMA)时隙分配方法。首先,根据高动态航空网络环境中媒体访问控制(MAC)协议的特点,推导出可以共用一个时隙进行通信的连接集合的计算方法,并建立了面向连接的空间复用TDMA(STDMA)时隙分配优化数学模型。然后,提出一种分布式STDMA时隙分配算法IDTA。IDTA不需要中心节点收集网络信息,分为2个同步的进程在发送节点和接收节点同时运行,而且能够根据连接的优先级按需分配时隙。最后,在OMNeT++仿真平台上建立计算机仿真模型,仿真结果显示:IDTA比其他分布式STDMA时隙分配算法更加适用于高动态的航空网络环境。     

中继卫星系统地面云存储架构设计

针对中继卫星系统日益增长的海量数据存储需求,探索将云技术应用于中继卫星地面存储系统中,研究并设计了适用于中继卫星系统的分布式云存储的体系架构.该架构通过分布式存储和存储虚拟化技术,对存储资源进行了整合,将分布在不同地理位置上的存储网络,集合成一个大规模广域云存储系统,可提供整体存储和访问的功能,并实现对数据的高效“存”、“取”、“管”.与传统NAS(Network Attached Storage,网络附加存储)架构分析比较,该架构从系统扩展性、可靠性和服务性等多个方面均更加具有优势,能够适应日益增长的中继卫星系统海量数据存储需求,解决中继卫星系统中大容量数据存储的瓶颈.     

一种适用的Multi-Agent System协同框架及其应用

概述了一种MAS协同框架通用的部分-全局规划(GPGP)和任务描述语言TAEMS.GPGP是一种不依赖于问题域的通用的MAS协同框架;它提供一个协同机制库,在不同的任务环境和协同要求下,应用不同机制集,从而动态地、柔性地描述任务环境,为GPGP应用提供根据与基础.本文在一个分布式的制造执行系统MM-MES中应用了合同网协议、TAEMS和GPGP,研究分布式的车间调度和协同.     

反舰导弹智能化作战在线任务分配研究

在预分配基础上,研究反舰导弹多弹协同作战的在线任务重分配.建立了多弹协同任务分配模型,采用基于拍卖协议的一致性方法研究在有中心弹和无中心弹情况下,分布式多弹协同任务重分配.实例仿真结果表明,分布式协同拍卖方法对解决多弹协同任务重分配问题是切实可行的,满足了作战系统对实时性和快速性的要求.     

基于独立任务的分布式容错调度算法

主副版本法是常见的容错方法,将每个任务的主版本和副版本分配到两个不同的处理机上执行,只要任务的主版本分配到一个处理机,则对应的副版本可以在另一个处理机上重叠执行.笔者研究了分布式控制系统中,基于主副版本容错算法的副版本可以在执行时间上重叠来调度分配独立的任务,该容错算法以副版本执行时间重叠部分的最小化为复制代价,通过仿真实验与集中式调度和分布式调度算法进行对比分析.     

量子密钥通信在分布式航天测控网中的应用研究

随着分布式航天测控网技术的不断发展,分布式航天测控网面临着信息安全问题.本文通过分析和研究各种信息加密技术,针对经典加密技术不能保证信息绝对保密性的弊端,考虑利用以量子力学为基础的量子密钥分配技术来保证测控信息传输的绝对安全.基于密钥这种"绝对保密"的方法与分布式航天测控网技术结合的思想,本文提出了量子密钥通信与分布式航天测控网相结合的密钥分配模型.     

深空中继通信束聚合效能研究

针对深空中继通信环境中BP/LTP协议加入束聚合策略对数据传输效率的影响问题,建模分析LTP数据块传输时间,考虑多会话并发及中继节点参与,获得应用数据在深空中继环境中总传输时间的期望,分析出束聚合策略对深空中继通信性能的影响。通过数值实验对不同束聚合值在典型深空中继通信环境中的效率进行了检验。结果表明:在应答链路不阻塞的约束下,越小的束聚合规模传输效率越高,且节点发送缓存大小对性能有重要影响。     

基于时间灵活度的中继卫星调度算法

中继卫星的调度问题是一个多资源多任务的复杂NP问题.作者在分析中继卫星系统资源、任务和约束的基础上,提出了一种基于任务时间灵活度的中继卫星调度算法,最后运用本算法对一个调度算例进行了验证求解.     

协同制造技术在大型飞机研发中的应用

通过协同信息技术构建协同工作平台,组成虚拟的协同工作团队,形成一个分布式、动态的协同工作环境是决定大型飞机研发成败的关键技术之一.     

基于联邦自适应滤波的分布式传递对准方法CSCD

为解决复杂飞行环境下由于机翼的挠曲变形等因素导致分布式传递对准的精度下降和稳定性差的问题,提出了一种基于27维状态变量传递对准模型的新型联邦自适应滤波算法。首先,子滤波器采用基于R和P自适应更新的卡尔曼滤波算法并结合27维传递对准模型进行单点传递对准。然后,主滤波器采用基于误差协方差矩阵的原则,对多个子滤波器的冗余信息和信息权重进行信息融合以及自适应分配。基于实际飞行数据的半物理仿真实验表明:该方法在一定程度上提高了分布式传递对准的稳定性和精度,姿态估计稳定性得到明显提高,动态杆臂以及航向角估计精度分别提高了61.54%和42.35%。     

Achieving the capacity of half-duplex degraded relay channels using polar coding

In this paper, a novel transmission protocol based on polar coding is proposed for the half-duplex degraded relay channel. In the proposed protocol, referred to as the partial message relaying, the relay only needs to forward a part of the decoded source message that the destination needs according to the exquisite nested structure of polar codes. Theoretically, it is proved that the scheme can achieve the capacity of the half-duplex relay channel under the decode-and-forward （DF） cooperation strategy while enjoying low encoding/decoding complexity. Practically, in order to minimize the global transmission power, the optimization of the power allocation is performed between the source and the relay by using information theoretic tools. Furthermore, a joint iterative soft parallel interference cancellation receiver structure is developed to suit to the proposed scheme. Simulation results show that the proposed scheme outperforms the conventional scheme designed by low-density parity-check （LDPC） codes.     

Relaying Selection with Network-coded Cooperative Protocols in Aeronautical Communications

In this article, we exploit the idea of network-coded cooperative protocol in aeronautical communications which combines different source nodes'information at the relay and joint decoding at the destination. Recently, the network coding in cooperative communications has been categorized into two mainstreams, bit-level and signal-level combinations, which are both discussed in the article. And to be exclusively, multiple access relay channel(MARC) is adopted. The mutual information expressions of both above-cited network-coded protocols are deduced, which prove that without proper selected relays to perform network coding, the spatial diversity of the proposed protocol cannot be obtained. This then leads to search for the selection and grouping algorithms. An adjacency matrix is defined to describe the connectivity of the nodes in one radio contact disk, so that, the selection and grouping of algorithm is equivalent to constructing this adjacency matrix to minimize the system outage probability evaluated in term of the mutual information. Besides, a network-coded cooperative protocol requires the acyclic network, of which the construction is to avoid loop-4 in the matrix. The article ends with simulations to demonstrate the viability of the proposed algorithms.     

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.     

Cooperative Routing for Maximizing Network Performance of Wireless Networks

To greatly increase spectral efficiency and improve network performance in wireless networks,a novel cooperative routing algorithm,namely maximum throughput cooperative routing(MTCR) algorithm,is proposed.According to cooperative link model,throughput analysis is presented to evaluate performance improvement in the process of exploiting cooperative commu-nication from physical layer to higher layer.Taking the throughput improvement as performance metric,a cooperative relay se-lection scheme is developed.Finally,based on the route constructed by adaptive forwarding cluster routing(AFCR) algorithm,each node on the route selects the optimum cooperative node from all the potential cooperative nodes to construct the coopera-tive link with maximum throughput so that cooperative route with maximum network throughput from source to destination can be set up.Simulation results show that compared with the noncooperative routing algorithm and minimum power selection de-code-and-forward(MPSDF) routing algorithm,the proposed algorithm can obviously improve network throughput in the pres-ence of low transmission power,large number of nodes and high spectral efficiency.     

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.     

A hybrid genetic approach for airborne sensor vehicle routing in real-time reconnaissance missions

Past initiatives to address surveillance and reconnaissance mission planning mainly focused on low-level control aspects such as real-time path planning and collision avoidance algorithms in limited environment. However, few efforts have been spent on high-level real-time task allocation. It is believed that automated decision capabilities supporting real-time resource allocation for sensor control and interactions might significantly reduce user workload, focusing attention on alternate tasks and objectives while assigning hard computational tasks to artificial agents. In this paper, we propose a new hybrid genetic algorithm to solve the dynamic vehicle routing problem with time windows, in which a group of airborne sensors are engaged in a reconnaissance mission evolving in a dynamic uncertain environment involving known and unknown targets/threats. In that context, visiting a target may consist in carrying out a collection of subtasks such as search, detect, recognize and confirm suspected targets, discover and confirm new ones. The approach consists in concurrently evolving two populations of solutions to minimize total travel time and temporal constraint violation using genetic operators combining variations of key concepts inspired from routing techniques and search strategies. A least commitment principle in servicing scheduled customers is also exploited to potentially improve solution quality.     

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。     

Reinforcement learning based dynamic distributed routing scheme for mega LEO satellite networks

Recently, mega Low Earth Orbit (LEO) Satellite Network (LSN) systems have gained more and more attention due to low latency, broadband communications and global coverage for ground users. One of the primary challenges for LSN systems with inter-satellite links is the routing strategy calculation and maintenance, due to LSN constellation scale and dynamic network topology feature. In order to seek an efficient routing strategy, a Q-learning-based dynamic distributed Routing scheme for LSNs (QRLSN) is proposed in this paper. To achieve low end-to-end delay and low network traffic overhead load in LSNs, QRLSN adopts a multi-objective optimization method to find the optimal next hop for forwarding data packets. Experimental results demonstrate that the proposed scheme can effectively discover the initial routing strategy and provide long-term Quality of Service (QoS) optimization during the routing maintenance process. In addition, comparison results demonstrate that QRLSN is superior to the virtual-topology-based shortest path routing algorithm.     

Effective local dynamic routing strategy for air route networks

With the rapid development of air transportation, network service ability has attracted a lot of attention in academe. Aiming to improve the throughput of the air route network(ARN), we propose an effective local dynamic routing strategy in this paper. Several factors, such as the routing distance, the geographical distance and the real-time local traffic, are taken into consideration.When the ARN is in the normal free-flow state, the proposed strategy can recover the shortest path routing(SPR) strategy. When the ARN undergoes congestion, the proposed strategy changes the paths of flights based on the real-time local traffic information. The throughput of the Chinese air route network(CARN) is evaluated. Results confirm that the proposed strategy can significantly improve the throughput of CARN. Meanwhile, the increase in the average flying distance and time is tiny. Results also indicate the importance of the distance related factors in a routing strategy designed for the ARN.     

通信约束下异构多无人机任务分配方法

针对异构多无人机协同执行侦察和打击任务中,存在通信距离、时间延迟等约束条件下的局部任务分配问题,提出了一种基于合同网的分布式多无人机任务分配方法。首先建立了异构集群发现新目标时的局部任务分配问题模型,设计了局部无人机通信网络中的信息一致性算法,实现了任务分配过程中任务发布阶段各无人机的冲突消解。设计了任务分配过程中的联盟构建和无人机资源管理方法,使联盟中各无人机能够以更加平衡的方式消耗资源。仿真结果表明,该方法能够解决通信约束下,异构多无人机执行察打任务时,所触发的针对目标打击任务的任务分配问题,且能够获得最大的系统效能。