基于智能反射面辅助的无人机中继系统安全通信方法

为了提高无人机中继系统的安全通信性能,解决无线信道受障碍物遮挡问题,该文提出一种基于智能反射面(IRS)辅助的无人机(UAV)中继系统安全通信方法。在所提方法中,通过联合优化UAV的位置、基站波束成形和IRS相移,最大化系统的最小保密速率。为了解决这个复杂的非凸优化问题,该文将原问题分解为UAV位置优化子问题、波束成形和IRS相移优化两个子问题。使用1阶泰勒展开处理优化问题中的非凸项,然后提出一种交替优化的算法进行求解。仿真结果表明该文提出的算法能提高系统的最小保密速率,并且具有良好的收敛性。     

全双工中继协作下的移动边缘计算系统能耗优化算法

为缓解终端设备处理大数据量、低时延业务的压力,该文提出一种基于全双工中继的移动边缘计算网络资源分配算法。首先,在满足计算任务时延约束、用户最大计算能力、用户和中继的最大发射功率约束条件下,考虑中继选择与子载波分配因子、用户任务卸载系数、用户与中继的传输功率的联合优化,建立了系统总能耗最小化问题。其次,利用交替迭代和变量代换的方法,将原非凸问题分解为两个凸优化子问题,并利用内点法和拉格朗日对偶原理分别进行求解。仿真结果表明,所提算法具有较低的能量消耗。     

全双工辅助的无人机上行通信抗窃听物理层安全技术研究

针对无人机上行通信链路的窃听攻击,提出一种全双工协同干扰的安全传输策略。方案利用收发双方在数据传输不同阶段的信息差异以及掌握的先验信息特征,向待传输信号注入人工噪声信号,从而使窃听链路形成干扰受限系统。在发射功率、无人机的机动性等约束条件下,建立最大化系统保密速率的联合优化问题,基于交替优化方法和连续凸近似技术将非凸问题转化为两个子问题,并设计了一种迭代优化算法进行求解。仿真结果表明,所提安全传输方案与其他参照方案相比,能够显著提高全双工无人机中继通信系统的保密速率,表现出更好的性能。     

基于IRS辅助的SWIPT物联网系统安全波束成形设计

为满足绿色万物互联的智能信号处理部署和物理层安全的新要求,针对基于智能反射面辅助的无线携能通信物联网系统中可持续能量供应紧缺问题,提出了一种安全波束成形设计方法。考虑保密速率、发射功率和IRS反射相移约束,以最大化能量采集器采集功率为目标,联合优化基站发射波束成形矩阵和干扰机协方差矩阵以及IRS相移,将优化问题建模为具有二次型约束的非凸二次型规划问题。利用松弛变量、半定松弛法、辅助变量和序列参数凸逼近法将非凸的二次型问题转化为等价的凸问题,并提出一种交替迭代优化算法获取原问题的可行解。仿真结果表明,所提算法能够快速收敛,且与基准方案相比能有效地提升性能。     

多标签无线供电反向散射通信网络能效优化算法

为了提高物联网(IoT)节点的运行周期和能量利用率,该文提出一种多标签无线供电反向散射通信网络能效最大化资源分配算法。考虑传输速率约束、能量收集约束以及发射功率约束,建立了基于系统能效最大化的资源分配模型。利用Dinkelbach理论、2次变换以及变量替换法,将原分式非凸问题转化为可求解的凸优化问题。通过拉格朗日对偶理论求得优化问题的全局最优解。仿真结果表明,该算法具有较好的收敛性和能效。     

IRS和人工噪声辅助的MIMO-SWIPT系统安全传输方案设计

针对多天线无线携能通信系统中能量收集节点作为潜在窃听者的信息安全问题，提出了一种智能反射面(Intelligent Reflecting Surface, IRS)和人工噪声辅助的物理层安全传输方案。首先考虑发射功率、能量收集门限以及IRS单位模约束，以最大化系统安全速率为优化目标，在合法用户直射链路不可用的情况下，联合设计发射端波束赋形矩阵、人工噪声协方差矩阵以及IRS相移矩阵，建模一非线性多变量耦合的非凸优化问题；接着利用均方误差准则等价转换非凸目标函数，并利用连续凸逼近方法(Successive Convex Approximation, SCA)处理非凸的能量收集约束；最后基于交替优化框架，分别用拉格朗日对偶方法和基于价格机制的优化最小化(Majorization-Minimization, MM)算法求解发射端变量和IRS端变量。仿真结果表明，与现有方案相比，所提算法能够在保障能量收集需求的同时大幅度提升系统的安全性能。     

多无人机辅助移动用户通信的功率分配和航迹优化

针对多无人机辅助移动用户通信的下行无线传输系统,提出了一种用户吞吐量最大化的多无人机发送功率和飞行航迹分簇优化方法。考虑每架无人机服务的用户分簇、发送功率分配和飞行航迹规划,构建了一个多无人机辅助多用户通信的吞吐量最大化问题。通过引入辅助变量和分离耦合变量的方法,将非凸问题分解为两个近似凸优化问题;再基于贪婪算法的思想和连续凸逼近方法,对两个近似凸优化问题进行迭代交替优化,得到原非凸问题的一个近似次优解。仿真结果表明,所提优化方法能够有效提高用户数据吞吐量。     

双智能反射平面辅助无线携能通信系统的安全通信优化

研究采用两个智能反射平面保障无线携能通信系统信息传输的物理层安全。通过联合优化两个智能反射平面的反射波束成形和基站的发射波束成形以最大化系统的总信息传输速率,同时满足基站的发射功率约束、能量收集用户的最小能量收集约束与最大窃听速率约束,以及智能反射平面反射系数的模一约束。由于存在两个智能反射平面之间的反射链路,所构建优化问题的优化变量高度耦合,难以直接求解。提出一种基于交替优化、半正定松弛和连续凸逼近的算法求问题的次优解。仿真结果表明,与现有的基准方案相比,所提算法能在保证信息传输安全和满足能量传输要求的情况下大幅提高系统的总数据速率。     

基于IRS辅助的MIMO车联网系统联合波束成形设计

针对MIMO车联网系统中V2I和V2V共享频谱的情形,提出了一种IRS辅助的联合波束成形设计方法。在保证V2V用户数据速率需求、V2I基站发射功率受限和IRS反射相移模约束等条件下,以最大化V2I用户的信道容量为目标,联合优化基站端发送预编码和IRS端的反射相移矩阵。采用最小均方误差规则、矩阵分析理论和内逼算法把非凸且变量耦合的优化问题转换为解耦后的凸优化问题,并提出一种交替迭代优化算法获得原问题的解。对所提算法的性能进行仿真,分析了IRS反射单元数、IRS部署位置和车速对车联网频谱效率的影响。仿真结果表明,所提算法收敛性较好,若在基站附近部署IRS,利用所提的联合波束成形方法能最大限度地提高车联网频谱效率。     

基于速率约束的OFDM中继链路能效最优资源分配策略

该文研究解码转发(DF)模式的OFDM中继链路的能效最大化资源分配问题。与现有典型的固定速率最小化发射功率或无约束最大化能效算法不同,该文考虑电路功率消耗的前提下,将问题建模为以最大化系统能效为目标,同时考虑用户最小速率需求、源节点S和中继节点R各自总发射功率约束下的联合子载波配对和最优功率分配问题。证明了速率和功率联合约束条件下中继链路全局能效最优解的唯一性,在此基础上提出一种低复杂度联合最优资源分配策略。仿真结果表明,该文所提方案能够在最小速率和S/R节点最大发射功率约束下自适应分配功率资源,实现系统能效最优,并能够降低链路的中断概率。     

Energy‐Aware Hybrid Cooperative Relaying with Asymmetric Traffic

In this paper, we study an asymmetric two‐way relaying network where two source nodes intend to exchange information with the help of multiple relay nodes. A hybrid time‐division broadcast relaying scheme with joint relay selection (RS) and power allocation (PA) is proposed to realize energy‐efficient transmission. Our scheme is based on the asymmetric level of the two source nodes’ target signal‐to‐noise ratio indexes to minimize the total power consumed by the relay nodes. An optimization model with joint RS and PA is studied here to guarantee hybrid relaying transmissions. Next, with the aid of our proposed intelligent optimization algorithm, which combines a genetic algorithm and a simulated annealing algorithm, the formulated optimization model can be effectively solved. Theoretical analyses and numerical results verify that our proposed hybrid relaying scheme can substantially reduce the total power consumption of relays under a traffic asymmetric scenario; meanwhile, the proposed intelligent optimization algorithm can eventually converge to a better solution.     

Sum-rate maximization for UAV-enabled two-way relay systems

In this paper, an Unmanned Aerial Vehicle (UAV)-enabled two-way relay system with Physical-layer Network Coding (PNC) protocol is considered. A rotary-wing UAV is applied as a mobile relay to assist two ground terminals for information interaction. Our goal is to maximize the sum-rate of the two-way relay system subject to mobility constraints, propulsion power consumption constraints, and transmit power constraints. The formulated problem is not easy to solve directly because it is a mixed integer non-convex optimization problem. Therefore, we decompose it into three sub-problems, and use the mutation arithmetic of the Genetic Algorithm (GA) and Successive Convex Approximation (SCA) to dispose. Besides, a high-efficiency iterative algorithm is proposed to obtain a locally optimal solution by jointly optimizing the time slot pairing, the transmit power allocation, and the UAV trajectory design. Numerical results demonstrate that the proposed design achieves significant gains over the benchmark designs.     

Secrecy Energy Efficiency Maximization for UAV-Enabled Multi-Hop Mobile Relay System

To deal with the secrecy issues and energy efficiency issues in the unmanned aerial vehicles ( UAVs) assisted communication systems, an UAV-enabled multi-hop mobile relay system is studied in an urban environment. Multiple rotary-wing UAVs with energy budget considerations are employed as relays to forward confidential information between two ground nodes in the presence of multiple passive eavesdroppers. The system secrecy energy efficiency ( SEE), defined by the ratio of minimum achievable secrecy rate ( SR) to total propulsion energy consumption (PEC), is maximized via jointly optimizing the trajectory and transmit power of each UAV relay. To solve the formulated non-convex fractional optimization problem subject to mobility, transmit power and information-causality constraints, an effective iterative algorithm is proposed by applying the updated-rate-assisted block coordinate decent method, successive convex approximation (SCA) technique and Dinkelbach method. Simulation     

Nelder‐Mead–based power optimization for secrecy enhancement in amplify‐and‐forward cooperative relay networks

Cooperative communication based on relaying nodes has been considered as a promising technique to increase the physical layer security (PLS) performance in wireless communications. In this paper, an optimal power allocation (OPA) scheme based on Nelder‐Mead (NM) algorithm is proposed for improving the secrecy rate of amplify‐and‐forward (AF) cooperative relay networks employing cooperative jamming (CJ) scheme. The proposed hybrid jamming scheme allows the source and selected relay to transmit the jamming signal along with the information to confound the eavesdropper. The path selection probability of ant colony optimization (ACO) algorithm is used for selecting the relay for transmission. The performance based on secrecy rate is evaluated for “n” trusted relays distributed dispersedly between the source and destination. Gradient‐based optimization and three‐dimensional exhaustive search methods are used as benchmark schemes for comparison of the proposed power optimization algorithm. The secrecy performance is also compared with conventional AF scheme and CJ scheme without power optimization (EPA). The impact of single and multiple relays on secrecy performance is also evaluated. Numerical results reveal that, compared with the gradient method and exhaustive search algorithm, the proposed power allocation strategy achieves optimal performance. Also, the derived OPA results show a significantly higher secrecy rate than the EPA strategy for both CJ and AF schemes.     

基于认知无人机移动中继网络的物理层安全通信研究

针对无线频谱资源稀缺和空对地视距(Line of Sight,LoS)链路的安全隐患问题,提出了一种无人机.(Unmanned Aerial Vehicle,UAV)中继辅助的认知无线电网络(Cognitive Radio Network,CRN)安全传输方案,研究了在主用户和窃听者存在的情况下,次用户发射机向次用户接...     

Two-way cooperative communications with statistical channel knowledge

We consider the problem of distributed beamforming for a two-way relay network which consists of two transceivers and multiple relay nodes. The main assumption in this work, which differentiates it from previously reported results, is that one of the transceivers is assumed to have only statistical information about channels between the other transceiver and the relay nodes. This assumption imposes less stringent restrictions on the bandwidth required to obtain channel state information via training. Based on this statistical modeling, we propose to use a chance-constrained programming approach to design a distributed beamforming algorithm. In this approach, we aim to minimize the total transmit power (consumed in the entire network) as perceived by one of the transceivers, subject to two probabilistic constraints. These constraints guarantee that the outage probability of the transceivers' received SNRs, as perceived by the master transceiver, is not less than certain given thresholds. We prove rigorously that such an approach leads to a relay selection algorithm where the relay with the strongest channel coefficient to the master transceiver participates in relaying and the remaining relays are shut off. As such, the optimal distributed beamforming algorithm is simplified to a power control solution. Closed-form solution to this problem is obtained and its performance is evaluated through numerical examples.     

Power allocation and effective capacity of AF successive relays

In the relay based telecommunications with K relays between the source and destination, \(K+1\) time or frequency slots are required for a single frame transmission. However, without the relays, only one time or frequency slot is used for a single frame transmission. Therefore, despite the benefits of relaying systems, this type of communications is not efficient from the spectral efficiency viewpoint. One solution to reduce this issue might be the full-duplex (FD) relays. An old technique which is reconsidered recently to improve the spectral efficiency of telecommunication systems. However, FD relays have a certain complexity, so, some similar techniques such as successive relays with nearly the same performance but less complexity is taken into account now. In successive relaying systems, two relays between the source and destination are employed which receive the transmitted frames from the source and relay it to the destination successively. This structure generally acts like an FD relays. In this paper, the effective capacity performance of an amplify and forward successive relaying systems with power allocation strategy at the relays are studied perfectly. However, while the inter-rely interference (IRI) between two successive relays has to be managed well, the power allocation and the effective capacity is derived under different assumptions about the IRI. In this way, we assume weak or strong, short or long-term constraints on the IRI. Then we extract the optimal transmitted power at the relay to maximize the effective capacity under these constraints.     

放大转发双向中继系统中降低总功率的波束成形设计

本文研究了多天线放大转发双向中继系统中在满足源节点信噪比要求条件下最小化系统总功率的波束设计问题。该问题是非凸优化问题,为了有效求解该问题,采用分层优化方法将原问题分解成发送波束成形向量优化、接收波束成形向量优化和中继波束成形矩阵优化三类子问题。发送/接收波束成形向量通过求解Rayleigh商最小化问题来获得。中继波束成形矩阵优化问题通过半正定松弛方法转化成半正定优化问题来求解。在求解这三类优化问题的基础上,提出了一种迭代波束成形算法,并采用单调有界序列定理证明了所提算法的收敛性。计算机仿真表明:所提算法经过若干次迭代即可收敛到稳定点;相比于已有算法,本文算法能显著降低系统总功率。      

On the Gaussian MIMO Relay Channel With Full Channel State Information

This paper addresses the problem of source and relay transmit covariance optimization on the Gaussian MIMO relay channel with full channel state information (CSI), i.e., assuming perfect knowledge of all channels. For full-duplex relaying, we show that the cut-set bound on capacity can be computed as the solution of a convex problem, thus providing a tighter bound than previously published. For time division duplex (TDD) relaying, both upper and lower bounds on capacity are derived, and the transmit covariance matrices are optimized for decode-and-forward (DF) strategies with either partial or full decoding at the relay. A generic procedure is introduced to formulate these problems into a standard convex form, and to solve them efficiently. Suboptimum precoders are also proposed which have a specific matrix structure that either leads to a closed-form expression or at least reduces the dimension of the optimization problem. Practical aspects related to transmit power constraints and CSI availability are then discussed. Finally, simulations in a cellular downlink scenario show that the partial DF strategy can achieve a rate very close to capacity for realistic values of the source to relay SNR, and that the rate loss due to suboptimum precoder structures remains small for typical antenna configurations.      

双向能量协作的中继系统功率分配算法

在无线中继系统中,考虑源节点和中继节点都是能量采集的,而源与中继之间可以进行能量协作,即可双向传递能量,针对瑞利衰落信道场景以最大化系统吞吐量为目标,联合优化源节点的发射功率、中继节点的发射功率以及传递的能量值,提出了双向能量传递的最优功率分配算法。本文根据场景模型建立了最优化问题,利用凸优化知识求得最优解的形式,假设能量传递无损耗情况下提出了理想功率分配方案;然后以此为基础,在满足能量因果性和数据因果性的条件下,对传递的能量和发送的功率进行优化。仿真结果表明,本文提出的双向能量传递的功率分配算法优于其它的功率分配算法,能有效的提高系统吞吐量。