基于半定规划和秩-1分解的稳健波束形成

针对标准Capon波束形成器在存在导向矢量失配时性能急剧下降问题, 提出了一种基于半定规划和秩-1分解的稳健波束形成算法. 该方法通过对实际导向矢量的估计提高自适应波束形成算法稳健性. 首先分别从干扰抑制和噪声抑制两个方面推导了新导向矢量应满足的约束条件, 并证明了利用矩阵滤波器构造约束条件的合理性; 构造了估计最优导向矢量的优化问题并将其转化为易于求解的松弛半定规划问题, 同时引入秩-1分解理论用于优化问题的求解. 仿真分析表明, 与目前较为常见的算法相比, 本文算法只需利用期望信号可能入射区间这一先验信息, 能获得更高输出信干噪比和功率估计精度. 关键词： 稳健自适应波束形成 半定规划 秩-1分解 导向矢量估计     

基于时频分析的多目标盲波束形成算法

针对现有盲波束形成算法适用范围较窄, 多目标信号分离级联模式结构复杂、并联模式稳定性较差等问题, 提出一种基于时频分析的多目标盲波束形成算法. 该算法首先利用时频分析技术给出信号导向矢量的不确定集, 然后优化求解导向矢量的最优估计, 最后利用Capon方法实现多目标信号的并行输出. 理论分析及仿真结果表明, 该算法对信号特性没有特殊要求, 适用性较广, 性能稳定, 且输出信干噪比高于其他盲波束形成算法, 接近于最优Capon波束形成器.     

智能反射面辅助的星地融合网络鲁棒安全波束成形算法

针对智能反射面辅助的星地融合网络,提出了一种基于窃听者非完美信道状态信息的鲁棒安全波束成形方法.首先,考虑到卫星利用点波束技术服务地球站,而地面基站通过多播技术服务多个地面用户,并且在两个网络实现频谱共享的情况,建立以系统总发射功率最小化为目标,基站用户服务质量和地球站安全可达速率为约束条件的联合优化问题;其次,为了求解该非凸问题,利用三角不等式和Holder不等式推导出窃听者非完美信道状态信息条件下的输出信干噪比上下界;接下来,进一步提出了基于半正定规划和惩罚函数相结合的鲁棒波束成形和功率控制联合优化方法,以实现星地融合网络的安全可靠传输.最后,计算机仿真结果验证了本文所提算法的有效性和优越性.     

基于支撑向量机算法的抗干扰混合波束成形系统

针对复杂电磁环境下毫米波阵列的空间辐射干扰抑制问题,设计了一种低成本的自适应波束成形系统。首先建立了复杂电磁环境下通信系统模型,建立目标函数。然后利用机器学习中支持向量机算法将原非凸约束问题转化为二阶锥优化问题,获得理想编码矢量。最后利用梯度追踪算法对理想波束矢量进行稀疏重构,完成抗干扰波束的低复杂度实现。仿真结果表明,提出的波束成形系统能够对干扰作出有效抑制,能提升通信质量。     

一种新的稳健波束形成算法及其一维搜索策略

存在条件失配时自适应波束形成器的性能急剧下降,凸优化技术的引入使稳健波束形成器的设计更加灵活,但同时带来了计算复杂度的增加和工程实现上的困难.针对上述问题,提出了一种基于最小二乘估计的稳健波束形成算法,并推导得到一种基于一维搜索的求解方法.首先利用广义旁瓣对消器的结构将标准Capon波束形成器转化为稳健最小二乘问题,并将该问题转化为二阶锥规划的形式.为了减少计算量,利用二阶锥规划问题的原始问题和对偶问题的关系,将求解过程转化为一维搜索,并利用牛顿迭代法获得最优解,从而获得与标准Capon波束形成相近的计算复杂度.仿真分析表明,该算法具有良好的抗导向矢量失配和快拍数不足的稳健性.     

利用导向向量旋转和联合迭代优化的自适应波束形成算法研究

针对大型阵列中自适应波束形成技术的实时性和鲁棒性问题,基于最小方差无失真响应(Minimum Variance Distortionless Response,MVDR)波束形成的信号模型框架,提出一种通过对导向矢量进行处理以降低干扰的自适应波束形成算法——稳健联合迭代优化-导向自适应(Robust Joint Iterative Optimization-Direction Adaptive,RJIO-DA)算法。在联合迭代优化的基础上,将降维变换矩阵的每一个列向量看作独立的方向向量,引导子空间内每一个维度上的权值迭代,同时旋转导向向量,减小了由于导向误差的不确定性而导致的性能下降。仿真实验结果表明,与现有的降维算法相比,RJIO-DA算法计算复杂度低、收敛率高、鲁棒性好,可在期望方向上稳健地聚集波束,更好地形成干扰方向的自适应零陷。      

一种基于矢量水听器阵的归一化加权Capon波束形成方法

矢量水听器同时拾取声场的标量信息声压和矢量信息振速。本文在分析了各向同性噪声场下矢量水听器阵Capon波束形成方位谱的基础上，提出了一种归一化加权Capon波束形成的改进算法，并给出了方位谱的表达式。本方法不需要特征分解，并且得到的是通常意义上的功率谱(可用于估计信号的能量)。仿真计算表明，此方法的性能优于Capon法，可大大提高方位估计的精度。     

旁瓣约束下期望主瓣幅度响应迭代波束设计

研究了旁瓣约束下的期望主瓣幅度逼近问题,其包含双边绝对值不等式结构,为非凸波束设计问题。针对传统的多约束优化算法难以处理非凸结构,提出了两种迭代算法。一种对原优化问题作局域线性近似,将非凸约束转换为仿射约束,进而迭代局部二阶锥规划问题求解原问题。另一种通过引入辅助变量构建增广拉格朗日函数,将加权向量与各约束解耦合,交替迭代求解关于原变量、主瓣辅助变量与旁瓣辅助变量的三个子优化问题以给出初始非凸问题的解。针对子优化问题,通过灵活运用拉格朗日乘子技术构建了低复杂度求解方案。采用仿真和实测阵列流形验证设计效果,结果表明,所提两种迭代算法可实现主瓣幅度逼近,合成平顶波束图,且对阵型无依赖性。交替迭代法耗时显著低于迭代二阶锥规划法。      

基于压缩感知理论的大规模MIMO系统下行信道估计中的导频优化理论分析与算法设计

针对大规模多输入多输出(multiple input multiple output, MIMO)系统信道估计中的导频设计问题,在压缩感知理论框架下,提出了一种基于信道重构错误率最小化的自适应自相关矩阵缩减参数导频优化算法.首先以信道重构错误率最小化为目标,推导了正交匹配追踪(orthogonal matching pursuit, OMP)算法下信道重构错误率与导频矩阵列相关性之间的关系,并得出优化导频矩阵的两点准则,即导频矩阵列相关性期望和方差最小化;然后研究了优化导频矩阵的方法,并提出相应的自适应自相关矩阵缩减参数导频矩阵优化算法,即在每次迭代过程中,以待优化矩阵平均列相关程度是否减小作为判断条件,调整自相关矩阵缩减参数值,使参数不断趋近于理论最优.仿真结果表明,与采用Gaussian矩阵、Elad方法、低幂平均列相关方法得到的导频矩阵相比,本文所提方法具有更好的列相关性,且具有更低的信道重构错误率.     

一种确定性盲波束形成的迭代算法

提出了一种基于信道的信号处理模型的在线迭代盲波束形成算法。该方法利用Givens变换,分步迭代地求出期望得到的信息矩阵,忽略无关的运算结果,达到减小运算量,减少内存占有空间的目的。同时,因为没有关于信源个数的先验假设,该方法可以在未知具体信源个数的情况下进行盲波束形成。在线迭代的算法结构也为DSP并行实现提供了可能。仿真试验验证了本方法的有效性和正确性。     

3D beamforming in Intelligent Reflecting Surface (IRS)-assisted multi-user cognitive radio networks

In this paper, we consider a multi-user cognitive radio network (CRN) equipped with an intelligent reflecting surface (IRS). We examine the network performance by evaluating the fairness of the secondary system, which is satisfying the minimum required signal to interference and noise ratio (SINR) for each secondary user (SU). The minimum SINR of the SUs is maximized by joint optimization of the beamforming vector and three-dimensional beamforming (3DBF) angles at the secondary base station (SBS) and also the phase shifts of the IRS elements. This optimization problem is highly non-convex. To solve this problem, we utilize Dinkelbach’s algorithm along with an alternating optimization (AO) approach to achieve some sub-problems. Accordingly, by further applying a semi-definite relaxation method, we convert these sub-problems to equivalent convex forms and find a solution. Furthermore, analytically we propose an algorithm for optimizing 3DBF angles at the SBS. Through numerical results, the improvement of the sum SINR of the secondary system using the proposed method is illustrated. Moreover, it is shown that as the number of reflecting elements of IRS increases, the sum SINR significantly augments while satisfying fairness. Also, the convergence of the proposed algorithm is verified utilizing numerical results.     

Wireless powered hybrid backscatter-active communications with hardware impairments

Wireless powered hybrid backscatter-active communication can full make use of the different tradeoff between power consumption and achievable rate of the active and backscatter communications, and thus achieving a better performance than wireless powered active or backscatter communications. In this paper, we design a throughput maximization-based resource allocation scheme for a wireless powered hybrid backscatter-active communication network, while considering the hardware impairments at all RF front ends of each transceiver. Towards this end, we formulate a problem by jointly optimizing the transmit power of the dedicated energy source, the time for pure energy harvesting, backscatter and active communications, the power reflection coefficient, and the transmit power of each IoT node during active communications. The formulated problem is non-convex and different to solve. Subsequently an iterative algorithm based on the block coordinated decent technology is proposed to address the above problem. Simulation results verify that our proposed iterative algorithm converges very fast and that the proposed scheme outperforms the baseline schemes in terms of the throughput.     

URLLC-oriented secure communication for UAV relay-assisted network

In this paper, we investigate the unmanned aerial vehicle (UAV) relay-assisted secure short packet communication. The UAV acts as a decode-and-forward relay to transmit control signals from the source to the actuators in the presence of a ground eavesdropper (EV) whose imperfect channel state information is available at the UAV. Specially, non-orthogonal multiple access is adopted in our work to achieve more connections and improve the fairness of communication and the short packets are employed for data transmission to reduce the latency. Explicitly, we maximize the minimum average secrecy throughput among all actuators by jointly optimizing the UAV trajectory, transmit power and blocklength allocation, which generates a challenging optimization problem. Therefore, we propose an iterative algorithm based on block coordinate descent method and successive convex approximation technique to handle the non-convex problem. Numerical results show that the proposed scheme has better performance compared to the benchmark schemes.     

Performance enhancement in the cell-free massive MIMO SWIPT system with active eavesdropping

This paper investigates the secure transmission for simultaneous wireless information and power transfer (SWIPT) in the cell-free massive multiple-input multiple-output (MIMO) system. To develop green communication, legitimate users harvest energy by the hybrid time switching (TS) and power splitting (PS) strategy in the downlink phase, and the harvested energy can provide power to send uplink pilot sequences for the next time slot. By in-built batteries, the active eavesdropper can send the same pilots with the wiretapped user, which results in undesirable correlations between the channel estimates. Under these scenarios, we derive the closed-form expressions of average harvested energy and achievable rates, and propose an iterative power control (PC) scheme based on max–min fairness algorithm with energy and secrecy constraints (MMF-ESC). This scheme can ensure the uniform good services for all users preserving the distributed architecture advantage of cell-free networks, while meeting the requirements of energy harvested by legitimate users and network security against active eavesdroppers. Besides, continuous approximation, bisection and path tracking are jointly applied to cope with the high-complexity and non-convex optimization. Numerical results demonstrate that MMF-ESC PC scheme can effectively increase the achievable rate and the average harvested energy of each user, and decrease the eavesdropping rate below the threshold. Moreover, the results also reveal that PS strategy is superior in harvesting energy in terms of more stringent network requirements for average achievable rates or security.     

Joint beamforming and phase-shifting design for energy efficiency in RIS-assisted MISO communication with statistical CSI

The emergence of more and more computation-intensive applications has imposed higher requirements in spectrum and energy efficiency (EE) for internet of things (IoT) wireless networks. Massive multiple-input multiple-output (MIMO) is utilized to gain spectral efficiency as an important part of wireless systems. However, the power expansion from hardware lowers the massive MIMO performance remarkably. Reconfigurable intelligent surface (RIS) technology can solve this problem well since it can not only provide higher array gain but also reduce energy depletion and hardware expense. In this article, we study joint optimization about beam-forming, RIS phase shift, and energy harvesting of IoT devices for maximizing EE of the multiple-input single-input downlink system with multiple IoT devices and an energy harvesting device. Different from existing works focusing on ergodic capacity with known statistic channel information of BS-RIS-device, we suppose that statistics information of RIS-device is known. Mathematically, the joint optimization problem is cast into a challenging non-convex one. To this end, based on successive convex approximation, we convert the original problem into two parts and then provide two heuristic schemes to tackle them, respectively. Next, an iterative scheme integrated by two heuristic algorithms is proposed to earn feasible solution in polynomial time. Finally, the proposed scheme is verified to be effective by simulations.     

Energy-efficient beamforming optimization for MISO communication based on reconfigurable intelligent surface

Reconfigurable intelligent surface (RIS), a planar metasurface consisting of a large number of low-cost reflecting elements, has received much attention due to its ability to improve both the spectrum and energy efficiency (EE) by reconfiguring the wireless propagation environment. In this paper, we propose a base station (BS) beamforming and RIS phase shift optimization technique that maximizes the EE of a RIS-aided multiple-input–single-output system. In particular, considering the system circuits’ energy consumption, an EE maximization problem is formulated by jointly optimizing the active beamforming at the BS and the passive beamforming at the RIS, under the constraints of each user’ rate requirement, the BS’s maximal transmit power budget and unit-modulus constraint of the RIS phase shifts. Due to the coupling of optimization variables, this problem is a complex non-convex optimization problem, and it is challenging to solve it directly. To overcome this obstacle, we divide the problem into active and passive beamforming optimization subproblems. For the first subproblem, the active beamforming is given by the maximum ratio transmission optimal strategy. For the second subproblem, the optimal phase shift matrix at the RIS is obtained by exploiting sine cosine algorithm (SCA). Moreover, for this case where each reflection element’s working state is controlled by a circuit switch, each reflection element’s switch value is optimized with the aid of particle swarm optimization algorithm. Finally, numerical results verify the effectiveness of our proposed algorithm compared to other algorithms.     

AN-aided beamforming for IRS-assisted SWIPT systems

This paper studies artificial noise (AN)-aided beamforming design in an intelligent reflecting surface (IRS)-assisted system empowered by simultaneous wireless information and power transfer (SWIPT) technique. Multiple power splitting (PS) single-antenna receivers simultaneously receive information and energy from a multi-antenna base station (BS). Although all users are legitimate, in each transmission interval only one receiver is authorized to receive information and the others are only allowed to harvest power which are considered as unauthorized receivers (URs). To prevent information decoding by URs, AN signal is transmitted from the BS. We adopt a non-linear model for energy harvesting. In the optimization problem, we minimize the total transmit power, and for this purpose, we utilize an alternating optimization (AO) algorithm. For the non-convex rank-one constraint for IRS phase shifts, we utilize a sequential rank-one constraint relaxation (SROCR) algorithm. In addition to single antenna URs scenario, we investigate multi-antenna URs scenario and evaluate their performance. Simulation results validate the effectiveness of using IRS.     

Joint user grouping and power allocation in VLC-NOMA system

With the energy consumption of wireless networks increasing, visible light communication (VLC) has been regarded as a promising technology to realize energy conservation. Due to the massive terminals access and increased traffic demand, the implementation of non-orthogonal multiple access (NOMA) technology in VLC networks has become an inevitable trend. In this paper, we aim to maximize the energy efficiency in VLC-NOMA networks. Assuming perfect knowledge of the channel state information of user equipment, the energy efficiency maximization problem is formulated as a mixed integer nonlinear programming problem. To solve this problem, the joint user grouping and power allocation (JUGPA) is proposed including user grouping and power allocation. In user grouping phase, we utilize the average of channel gain among all user equipment and propose a dynamic user grouping algorithm with low complexity. The proposed scheme exploits the channel gain differences among users and divides them into multiple groups. In power allocation phase, we proposed a power allocation algorithm for maximizing the energy efficiency for a given NOMA group. Thanks to the objective function is fraction form and non-convex, we firstly transform it to difference form and convex function. Then, we derive the closed-form optimal power allocation expression that maximizes the energy efficiency by Dinkelbach method and Lagrange dual decomposition method. Simulation results show that the JUGPA can effectively improve energy efficiency of the VLC-NOMA networks.     

Performance Analysis and Optimization of a Cooperative Transmission Protocol in NOMA-Assisted Cognitive Radio Networks with Discrete Energy Harvesting

In this paper, we propose a spectrum-sharing protocol for a cooperative cognitive radio network based on non-orthogonal multiple access technology, where the base station (BS) transmits the superimposed signal to the primary user and secondary user with/without the assistance of a relay station (RS) by adopting the decode-and-forward technique. RS performs discrete-time energy harvesting for opportunistically cooperative transmission. If the RS harvests sufficient energy, the system performs cooperative transmission; otherwise, the system performs direct transmission. Moreover, the outage probabilities and outage capacities of both primary and secondary systems are analyzed, and the corresponding closed-form expressions are derived. In addition, one optimization problem is formulated, where our objective is to maximize the energy efficiency of the secondary system while ensuring that of the primary system exceeds or equals a threshold value. A joint optimization algorithm of power allocation at BS and RS is considered to solve the optimization problem and to realize a mutual improvement in the performance of energy efficiency for both the primary and secondary systems. The simulation results demonstrate the validity of the analysis results and prove that the proposed transmission scheme has a higher energy efficiency than the direct transmission scheme and the transmission scheme with simultaneous wireless information and power transfer technology.