Convex optimization algorithms for cooperative RSS-based sensor localization

To obtain a global solution for the source location estimates, the cost function of RSS-based sensor localization is relaxed as convex optimization problem which can be solved by interior point method. Weighted squared least square (WSLS) and weighted least square (WLS) based optimization functions are proposed to locate the source nodes. The corresponding semidefinite programming (SDP), second-order cone program (SOCP) and mixed SOC/SDP algorithms are designed by considering the known or unknown transmit powers. The computational complexity of the proposed algorithms is derived by analyzing the number of variables and equality constraints produced in the relaxation. The simulations show that the mixed SOC/SDP runs faster than the SDP, although the algorithms have the approximately equal accuracy performance. Whether the transmit power is known or not, the accuracy performance of the WLS-SDP is better than that of the WSLS-SDP and WSLS-SOC/SDP algorithms. However the computational complexity of the WLS-SDP is greatly larger than that of WSLS-SOC/SDP and WSLS-SDP due to a large number of variables.     

一种基于混合NOMA的IRS-MEC系统能量效率优化方案

在移动边缘计算系统（MEC）中结合智能反射面（IRS）和资源分配策略以提高系统能量效率是当前国内外研究的热点。基于混合非正交多址（NOMA）传输模式,通过对用户的本地运算频率、传输功率、传输时间和智能反射面离散相移的联合优化,实现智能反射面辅助的移动边缘计算系统能量效率最大化。由于优化过程涉及难以求解的非凸分式规划问题,提出了Dinkelbach-SCA的两步迭代算法：首先利用Dinkelbach方法将初始问题转换成易于求解的形式,通过分离变量对智能反射面离散相移进行优化;其次为了解耦传输功率与时间之间的耦合关系,引入辅助变量,并结合逐次凸逼近（SCA）方法将非凸问题转换成凸问题,求出优化解。仿真结果表明采用的系统方案的能量效率优于其他对比方案,并发现系统的能量效率随用户2的最小计算数据量减少而提升。     

采用预编码的GSM网络最大互信息优化方法研究

为了提高广义空间调制(GSM)互信息的性能,提出了一种新的基于椭球算法的预编码方案。首先,为了对含有互信息的预编码器进行优化,推导出了有限字符输入下的GSM互信息解析表达式。在最大化GSM互信息的过程中,为了解决联合预编码设计的非凸耦合问题,将GMS系统转换成虚拟的多输入多输出(MIMO)系统。然后,在考虑所有子信道功率约束的条件下,使用了扩展的椭球算法。实验结果表明,提出的预编码方案大大提升了GSM互信息的性能。     

无线供能移动边缘计算系统的安全卸载优化

针对能量受限的多用户移动边缘计算（MEC）系统存在恶意窃听节点的问题,提出一种联合无线能量传输（WPT）和MEC的安全部分计算卸载方案。该方法以系统接入点（AP）能耗最小化为优化目标,在计算延迟、安全卸载和能量捕获约束条件下,联合优化AP能量传输协方差矩阵、本地CPU频率、用户卸载比特数、用户卸载时间分配以及用户传输功率。针对AP能耗最小化问题为非凸问题,首先采用凸差分算法（DCA）将原始非凸问题转换为凸问题,然后采用拉格朗日对偶法以半封闭形式获得问题最优解。当计算任务数为5×10⁵比特时,与本地计算和安全全部计算卸载方法相比,安全部分卸载方案的能量消耗分别降低了61.3%和84.4%;当窃听节点距离超过25 m时,安全部分卸载方案所消耗的能量远小于本地计算和安全全部计算卸载。仿真实验结果表明,在保证物理层安全卸载的情况下,所提方案能够有效降低AP能耗、提高系统性能增益。     

Iterative constrained weighted least squares estimator for TDOA and FDOA positioning of multiple disjoint sources in the presence of sensor position and velocity uncertainties

Sensor position and velocity uncertainties are known to be able to degrade the source localization accuracy significantly. This paper focuses on the problem of locating multiple disjoint sources using time differences of arrival (TDOAs) and frequency differences of arrival (FDOAs) in the presence of sensor position and velocity errors. First, the explicit Cramér–Rao bound (CRB) expression for joint estimation of source and sensor positions and velocities is derived under the Gaussian noise assumption. Subsequently, we compare the localization accuracy when multiple-source positions and velocities are determined jointly and individually based on the obtained CRB results. The performance gain resulted from multiple-target cooperative positioning is also quantified using the orthogonal projection matrix. Next, the paper proposes a new estimator that formulates the localization problem as a quadratic programming with some indefinite quadratic equality constraints. Due to the non-convex nature of the optimization problem, an iterative constrained weighted least squares (ICWLS) method is developed based on matrix QR decomposition, which can be achieved through some simple and efficient numerical algorithms. The newly proposed iterative method uses a set of linear equality constraints instead of the quadratic constraints to produce a closed-form solution in each iteration. Theoretical analysis demonstrates that the proposed method, if converges, can provide the optimal solution of the formulated non-convex minimization problem. Moreover, its estimation mean-square-error (MSE) is able to reach the corresponding CRB under moderate noise level. Simulations are included to corroborate and support the theoretical development in this paper.     

Monocular 3D tracking of deformable surfaces using sequential second order cone programming

Reconstructing structures of deformable objects from monocular image sequences is important for applications like visual servoing and augmented reality. In this paper, we propose a method to recover 3D shapes of deformable surfaces using sequential second order cone programming (SOCP). The key of our approach is to represent the surface as a triangulated mesh and introduce two sets of constraints, one for model-to-image keypoint correspondences which are SOCP constraints, another for retaining the original lengths of the mesh edges which are non-convex constraints. In the process of tracking, the surface structure is iteratively updated by solving sequential SOCP feasibility problems in which the non-convex constraints are replaced by a set of convex constraints over a local convex region. The shape constraints used in our approach is more generic than previous methods, that enables us to reliably recover surface shapes with smooth, sharp and other complex deformations. The capability and efficiency of our approach are evaluated quantitatively with synthetic image sequences and qualitatively with real image sequences.     

Optimal Metric Projections for Deformable and Articulated Structure-from-Motion

This paper describes novel algorithms for recovering the 3D shape and motion of deformable and articulated objects purely from uncalibrated 2D image measurements using a factorisation approach. Most approaches to deformable and articulated structure from motion require to upgrade an initial affine solution to Euclidean space by imposing metric constraints on the motion matrix. While in the case of rigid structure the metric upgrade step is simple since the constraints can be formulated as linear, deformability in the shape introduces non-linearities. In this paper we propose an alternating bilinear approach to solve for non-rigid 3D shape and motion, associated with a globally optimal projection step of the motion matrices onto the manifold of metric constraints. Our novel optimal projection step combines into a single optimisation the computation of the orthographic projection matrix and the configuration weights that give the closest motion matrix that satisfies the correct block structure with the additional constraint that the projection matrix is guaranteed to have orthonormal rows (i.e. its transpose lies on the Stiefel manifold). This constraint turns out to be non-convex. The key contribution of this work is to introduce an efficient convex relaxation for the non-convex projection step. Efficient in the sense that, for both the cases of deformable and articulated motion, the proposed relaxations turned out to be exact (i.e. tight) in all our numerical experiments. The convex relaxations are semi-definite (SDP) or second-order cone (SOCP) programs which can be readily tackled by popular solvers. An important advantage of these new algorithms is their ability to handle missing data which becomes crucial when dealing with real video sequences with self-occlusions. We show successful results of our algorithms on synthetic and real sequences of both deformable and articulated data. We also show comparative results with state of the art algorithms which reveal that our new methods outperform existing ones.     

鲁棒最小二乘支持向量回归机

针对最小二乘支持向量回归机(LS-SVR)对异常值较敏感的问题,通过设置异常值所造成的损失上界,提出一种非凸的Ramp损失函数。该损失函数导致相应的优化问题的非凸性,利用凹凸过程(CCCP)将非凸优化问题转化为凸优化问题。给出Newton算法进行求解并分析了算法的计算复杂度。数据集测试的结果表明,与最小二乘支持向量回归机相比,该算法对异常值具有较强的鲁棒性,获得了更优的泛化能力,同时在运行时间上也具有明显优势。     

无线传感器网络中远程链路传输算法研究

在COSEN算法基础上,提出一种多级分层链路算法。该算法根据各节点与基站的距离排序,固定各层节点数量来进行分层,每层节点形成一个簇链,并以剩余能量为基准由上级簇首在指定范围内选举下级簇首,各簇首负责收集本层数据并融合从下级簇首收到的数据,将融合后的数据发送给上级簇首,逐层传递直至基站。通过NS3平台仿真验证,结果表明,该算法的传输时延和能耗均优于PEGASIS算法及COSEN算法。     

Robust disturbance rejection for repetitive control systems with time‐varying nonlinearities

This paper presents a disturbance‐rejection method for a modified repetitive control system with a nonlinearity. Taking advantage of stable inversion, an improved equivalent‐input‐disturbance (EID) estimator that is more relaxed for system design is developed to estimate and cancel out the influence of the disturbance and nonlinearity in the low‐frequency domain. The high‐frequency influence is filtered owning to the low‐pass nature of the linear part of the closed‐loop system. To avoid the restrictive commutative condition and choose a Lyapunov function of a more general form, a new design algorithm, which takes into account the relation between the feedback control gains and the observer and improved EID estimator gains, is developed for the nonlinear system. Furthermore, comparisons with the generalized extended‐state observer (GESO) and conventional EID methods are conducted. A clear relation between the developed estimator and the GESO is also clarified. Finally, simulations show the effectiveness and the advantage of the developed method.     

基于缓存辅助的全双工无线携能通信系统的中继选择策略

为了提高无线携能通信（SWIPT）系统的性能,构建了一个全新的基于缓存辅助的全双工中继协作系统模型,并在系统中考虑了空闲能量接入点（EAP）作为中继节点的额外能量补充。对于系统吞吐量最优化问题,提出一种基于功率分配协作的SWIPT中继选择策略。首先,基于通信服务质量与源节点发射功率等约束建立问题模型;其次,通过数学变换将原非线性混合整数规划问题转换为一对耦合优化问题;最后,利用KKT条件并借助拉格朗日函数解决内部优化问题,得到了功率分配因子和中继发射功率的闭式解,并在此结果上解决外部优化问题,选择最佳中继进行协作通信。仿真实验结果表明,空闲EAP和中继处高速缓冲存储器的配置具有可行性和有效性,并且,所提系统在吞吐量增益方面明显优于传统的中继协作通信系统。     

导向矢量失配情况下基于稀疏表示的波达方向估计算法

提出了一种传感器阵列导向矢量失配情况下的基于稀疏表示的信号源波达方向DOA估计算法。针对一些实际环境中噪声重尾现象严重的特点,采用合成圆对称广义高斯噪声分布对其进行模拟。考虑到实际环境中传感器自身运动以及外界环境因素的改变可能会导致传感器导向矢量产生波动,利用加权最小二乘法对波动生成的增益值进行最优估计。然后,构建信号模型的分数低阶矩FLOM矩阵,进行矢量化处理,以提高其数组维数。最后,利用稀疏表示方法重构信号模型,将信号源DOA估计转化为二阶锥规划问题进行求解,并采用奇异值分解降低运算量。仿真结果表明,本算法的信号源DOA估计具有很高的分辨率,且有效地避免了导向矢量失配对DOA估计产生的影响。     

Optimal precoding for full-duplex base stations under strongly correlated self-interference channels

We study the optimal precoding for a full-duplex (FD) system, where one FD multi-antenna base station (BS) respectively transmits to and receives from two half-duplex single-antenna mobile users (MUs) on the same time slot and frequency band. At the FD BS, the received signal from the desired MU is severely affected by the extremely strong self-interference (SI) from its transmit antennas to the receive antennas. In the presence of residual SI after imperfect SI cancellation, the downlink transmission rate maximization problem subject to a targeted uplink rate is formulated as a non-convex optimization problem to characterize the achievable rate region for the considered system. Considering the case in which the SI channel is strongly correlated, the above problem is transformed into a convex problem by exploiting the rank-one property of the SI channel, which can be solved efficiently. Finally, numerical results validate the effectiveness of the proposed scheme.     

基于多粒度拓扑图的无线传感器网络逐级精化溯源方法

针对溯源数据分段传输方法要求所有分段准确到达基站（BS）后才能解码，鲁棒性较弱的问题，提出一种无线传感器网络（WSN）溯源逐级精化方法。首先，在BS端利用商空间划分理论将较大的WSN拓扑图划分为由少量抽象节点组成的较粗粒度的拓扑图；然后，利用字典编码溯源的方式分段传输溯源；最后，在BS端根据依次到达的分段进行逐级精化解码，实现了在BS端由粗到细逐级精化解码溯源的过程，且BS可以根据前期解码出的较粗粒度下的溯源信息判断是否放弃此数据还是须采用更细粒度的数据进行深入评估。理论分析、仿真与实验数据均表明，与传统分段方法相比，所提方法平均压缩比提高约51.8%，平均能量消耗降低约50.5%。     

Received signal strength based positioning for multiple nodes in wireless sensor networks

We address the problem of locating multiple nodes in a wireless sensor network with the use of received signal strength (RSS) measurements. In RSS based positioning, transmit power and path-loss factor are two environment dependent parameters which may be uncertain or unknown. For unknown transmit powers, we devise two-step weighted least squares (WLS) and maximum likelihood (ML) algorithms for node localization. The mean square error of the former is analyzed in the presence of zero-mean white Gaussian disturbances. When both transmit powers and path-loss factors are unavailable, two nonlinear least squares estimators, namely, the direct ML approach and combination of linear least squares and ML algorithm, are developed. Numerical examples are also included to evaluate the localization accuracy of the proposed estimators by comparing with two existing node positioning methods and the Cramér–Rao lower bound.     

An event-triggered approach to state estimation with multiple point- and set-valued measurements

In this work, we consider state estimation based on the information from multiple sensors that provide their measurement updates according to separate event-triggering conditions. An optimal sensor fusion problem based on the hybrid measurement information (namely, point- and set-valued measurements) is formulated and explored. We show that under a commonly-accepted Gaussian assumption, the optimal estimator depends on the conditional mean and covariance of the measurement innovations, which applies to general event-triggering schemes. For the case that each channel of the sensors has its own event-triggering condition, closed-form representations are derived for the optimal estimate and the corresponding error covariance matrix, and it is proved that the exploration of the set-valued information provided by the event-triggering sets guarantees the improvement of estimation performance. The effectiveness of the proposed event-based estimator is demonstrated by extensive Monte Carlo simulation experiments for different categories of systems and comparative simulation with the classical Kalman filter.     

无线传感器网络Top-k多查询算法

针对无线传感器网络中多个Top-k查询问题,提出了一种Top-k多查询处理的算法,对接收到的多个Top-k查询请求进行预处理,预处理依据是约束条件,得出两类不同的查询集合:单约束条件的多查询和多约束条件的多查询。针对单约束条件的多查询提出了ETOP算法,该算法首先对排在时间序列最前面的Top-k查询请求进行基于网内处理,然后把查询结果存入基站缓存,并把结果的最小值设定为阈值传输到各个节点,再根据后续查询请求的查询范围进行相应的查询,从而快速地获得Top-k查询结果。实验表明:Top-k多查询方法在能够很好地实现查询的同时,减少了无线传感器网络中的传输消耗和能量消耗。     

基于反馈神经网络的稀疏信号恢复的优化算法

针对稀疏信号的重构问题,提出了一种基于反馈神经网络（RNN）的优化算法。首先,需要对信号进行稀疏表示,将数学模型化为优化问题;接着,基于l₀范数是非凸且不可微的函数,并且该优化问题是NP难的,因此在测量矩阵A满足有限等距性质（RIP）的前提下,提出等价优化问题;最后,通过建立相应的Hopfield反馈神经网络模型来解决等价的优化问题,从而实现稀疏信号的重构。实验结果表明,在不同观测次数m下,对比RNN算法和其他三种算法的相对误差,发现RNN算法相对误差小,且需要的观测数也少,能够高效地重构稀疏信号。     

Utility-based downlink power allocation in multicell wireless packet networks

This paper introduces a utility-based radio resource management technique in multicell wireless packet networks. In terms of allocation of base station (BS) downlink transmit power and assignment of resource to users in each cell, we formulate a problem of maximizing system utility which is defined as the sum of cell utilities. The problem, however, is not solvable due to its non-convex property. Thus, we propose a heuristic algorithm based on an intuition obtained from analyzing a simple two-cell problem. Though the heuristic approach also incurs signaling overhead for power coordination between neighboring base stations, it is much less than that of the original approach. Simulation results show the performance of our proposed algorithm compared with two competitive schemes: optimal and maximum power allocation schemes. As expected, the optimal allocation scheme shows the best performance but can not be employed in a real network due to intractable complexity. Our heuristic algorithm performs reasonably well with very low complexity.     

鲁棒的双向多中继物理层安全传输方案

针对双向多中继系统物理层安全传输无法获取窃听者的精确信道状态信息（CSI）的问题,提出鲁棒的多中继协作波束形成和人工噪声联合物理层安全传输方案,以最大化系统总功率约束下信道状态"最差情况"时的安全总速率。在该方案中,待求解的问题是一个复杂的非凸优化问题。采用交替迭代和连续凸近似（SCA）方法,对波束形成向量、人工噪声协方差矩阵和源节点发射功率进行交替优化迭代,得到了问题的优化解。仿真实验验证了所提方案的有效性,并表明该方案具有更优的安全性能。