A novel 3D GBSM for mmWave MIMO channels

In this paper, a novel three dimensional (3D) wideband geometry-based stochastic model (GBSM) for millimeter wave (mmWave) multiple-input multiple-output (MIMO) channels is proposed. A homogeneous Poisson point process (PPP) is used to generate the clusters in 3D space. The transmitter (Tx) and receiver (Rx) are surrounded by two spheres. The scatterers distributed in the two spheres are introduced to mimic the clustering effects of multipath components (MPCs) in delay and angular domains. The large-scale path loss model and line-of-sight (LOS) probability model are taken into account to make the channel model realistic. In addition, mmWave channel measurements are conducted in an indoor environment. Simulation results based on the two-sphere channel model are compared with measurement results and good agreements are achieved, which validates the proposed channel model. The results indicate that the proposed channel model has good adaptivity and can model the mmWave channel accurately.     

基于改进粒子群算法的毫米波大规模MIMO混合预编码方案

针对毫米波大规模多输入多输出（MIMO）系统中基于传统粒子群优化（PSO）算法的混合预编码方案,在迭代后期收敛速度较慢以及容易陷入局部最优值的问题,提出了一种基于改进PSO算法的混合预编码方案。首先,随机初始化粒子的位置矢量和速度矢量,并以最大化系统和速率为目标求解初始群体最优位置矢量;其次,更新位置矢量和速度矢量,并随机地选择更新后的两个粒子的个体历史最优位置矢量进行加权求和作为新的个体历史最优位置矢量,从中挑选出若干个使系统和速率最大的粒子,将其个体历史最优位置矢量的加权平均值作为新的群体最优位置矢量,并与之前的群体最优位置矢量比较,经过多次迭代形成最终的群体最优位置矢量即为所求的最佳混合预编码矢量,并对其进行归一化;最后,根据归一化后的混合预编码矢量设计最终的模拟预编码矩阵和数字预编码矩阵。仿真结果表明,与基于传统PSO算法的混合预编码方案相比,所提改进方案在收敛速度与和速率上都得到优化;其收敛速度提高约100%,且性能可以达到全数字预编码方案的90%,因此,该改进方案能够有效提升系统性能且加快收敛。     

Compressive sampling optimization for user signal parameter estimation in massive MIMO systems

As the most promising technology in wireless communications, massive multiple-input multiple-output (MIMO) faces a significant challenge in practical implementation because of the high complexity and cost involved in deploying a separate front-end circuit for each antenna. In this paper, we apply the compressive sampling technique to reduce the number of required front-end circuits in the analog domain and the computational complexity in the digital domain. Unlike the commonly adopted random projections, we exploit the a priori probability distribution of the user positions to optimize the compressive sampling strategy, so as to maximize the mutual information between the compressed measurements and the direction-of-arrival (DOA) of user signals. With the optimized compressive sampling strategy, we further propose a compressive sampling Capon spatial spectrum estimator for DOA estimation. In addition, the user signal power is estimated by solving a compressed measurement covariance matrix fitting problem. Furthermore, the user signal waveforms are estimated from a robust adaptive beamformer through the reconstruction of an interference-plus-noise compressed covariance matrix. Simulation results clearly demonstrate the performance advantages of the proposed techniques for user signal parameter estimation as compared to existing techniques.     

A novel 3D fruit fly optimization algorithm and its applications in economics

Neural Computing and Applications - Fruit fly optimization algorithm (FOA) is a method that we have previously developed from the food-finding behavior of fruit flies to solve optimization...     

Constrained parameter estimation with applications to blending operations

The classical least squares approach to parameter estimation for dynamic models ignores a priori information about the feasible values of the estimated parameters. But in many practical problems, such information is available in the form of upper and lower limits. In this paper, two alternative techniques are evaluated for this important class of constrained parameter estimation problems for dynamic systems. Simulation results for two blending problems illustrate that more accurate parameter estimates and better predictions can be obtained by using a quadratic programming approach.     

同参数估计对偶的自适应控制算法

本文把线性和非线性系统统一处理。从自适应控制算法与参数估计算法的对偶性出发,提出了自适应控制算法的一种统一格式。这种格式算法简单,并在一定的条件下,能使控制误差一致的足够小。     

基于PN序列的频偏估计算法

本文提出了一种基于时域PN序列导频相关性的频偏估计算法,通过计算接收信号和发送信号共轭乘积的自相关函数,将频偏估计问题转化为一个单频谱估计问题,并且给出了简化的谱估计算法,从而避免了频率搜索,具有较低的实现复杂度,另外,此算法使用和符号同步相同的PN序列资源,节省系统频谱资源。在多径信道下也给出了相应的形式,经过理论分析和仿真证明了,在多径信道下,改进算法的获得了频率分集增益,提高了估计性能。     

Set membership parameter estimation in the frequency domain based on complex intervals

This paper is devoted to set membership parameter estimation for non-linear complex-valued models. In such a context, the error between the measured data and the output model is supposed to be bounded with known prior bounds. The proposed approach is based on set inversion via complex interval analysis. A first contribution of this paper is the extension of logarithm and exponentiel functions to polar intervals. In a second part, it is shown on an engineering application devoted to thermal parameter estimation, that the proposed interval complex representation is useful.     

基于声道低频能量比的MP3压缩域音频水印算法

为了解决目前大多音频水印算法在应用于MP3音频时存在的效率低下、鲁棒性与不可感知性较难平衡等问题,提出基于MP3帧声道间低频能量的压缩域音频水印算法。该算法的嵌入和提取过程可分别在MP3压缩和解压缩的过程中完成,能大大提高水印的嵌入提取效率。而且由于低频能量具有较好的稳定性,算法利用MP3编解码过程中生成的改进离散余弦变换（MDCT）系数计算得到声道内低频能量,将左右声道内低频能量之比以固定步长量化,最终根据量化结果调整相应的MDCT系数实现水印嵌入;同时,结合不同比例因子频带能量的占比在计算声道内低频能量前对水印嵌入频带进行了筛选,从而能保证水印鲁棒性与不可感知性的平衡。实验显示,该算法可以在维持原始音频可听性的基础上实现对各种类型攻击较好的鲁棒性,尤其是可以抵抗MP3重压缩的攻击。     

Precoder and combiner design for dynamically sub-connected hybrid architecture with low-resolution DACs/ADCs in mmWave massive MIMO systems

Dear editor, The integration of mmWave and massive multiple-input multiple-output (mMIMO) becomes inevitable in future 5G wireless communication systems[1],in w...     

A novel robust adaptive control algorithm with finite-time online parameter estimation of a humanoid robot arm

A novel robust adaptive control algorithm is proposed and implemented in real-time on two degrees-of-freedom (DOF) of the humanoid Bristol-Elumotion-Robotic-Torso II (BERT II) arm in joint-space. In addition to having a significant robustness property for the tracking, the algorithm also features a sliding-mode term based adaptive law that captures directly the parameter estimation error. An auxiliary filtered regression vector and filtered computed torque is introduced. This allows the definition of another auxiliary matrix, a filtered regression matrix, which facilitates the introduction of a sliding mode term into the adaptation law. Parameter error convergence to zero can be guaranteed within finite-time with a Persistent-Excitation (PE) condition or Sufficient Richness condition for the demand. The proposed scheme also exhibits robustness both in the tracking and parameter estimation errors to any bounded additive disturbance. This theoretical result is then exemplified for the BERT II robot arm in simulation and for experiments.     

Joint DOA and channel estimation with data detection based on 2D unitary ESPRIT in massive MIMO systems

We propose a novel method for joint two-dimensional (2D) direction-of-arrival (DOA) and channel estimation with data detection for uniform rectangular arrays (URAs) for the massive multiple-input multiple-output (MIMO) systems. The conventional DOA estimation algorithms usually assume that the channel impulse responses are known exactly. However, the large number of antennas in a massive MIMO system can lead to a challenge in estimating accurate corresponding channel impulse responses. In contrast, a joint DOA and channel estimation scheme is proposed, which first estimates the channel impulse responses for the links between the transmitters and antenna elements using training sequences. After that, the DOAs of the waves are estimated based on a unitary ESPRIT algorithm using previous channel impulse response estimates instead of accurate channel impulse responses and then, the enhanced channel impulse response estimates can be obtained. The proposed estimator enjoys closed-form expressions, and thus it bypasses the search and pairing processes. In addition, a low-complexity approach toward data detection is presented by reducing the dimension of the inversion matrix in massive MIMO systems. Different cases for the proposed method are analyzed by changing the number of antennas. Experimental results demonstrate the validity of the proposed method.     

A novel approach to robust parameter estimation using neurofuzzy systems

A novel approach for solving robust parameter estimation problems is presented for processes with unknown-but-bounded errors and uncertainties. An artificial neural network is developed to calculate a membership set for model parameters. Techniques of fuzzy logic control lead the network to its equilibrium points. Simulated examples are presented as an illustration of the proposed technique. The result represent a significant improvement over previously proposed methods.     

A frequency reconfigurable MIMO antenna with agile feedline for cognitive radio applications

A novel frequency agile multiple‐input‐multiple‐output (MIMO) patch antenna based on a reconfigurable feedline is proposed. The proposed antenna structure has two hexagonal‐shaped patch antenna elements. A defected ground structure having hexagonal shape is included in the ground plane to make the design compact and improve isolation among antenna elements. Further compactness is achieved using reactive loading. Frequency reconfigurability is realized by employing varactor diodes in the microstrip feedline. The proposed antenna achieves a frequency reconfigurable band with wide tuning range from 1.42 to 2.27 GHz with good gain and efficiency. Furthermore, an envelope correlation coefficient value of less than 0.2 and minimum isolation of 12 dB was achieved, displaying good MIMO performance. The presented antenna has a planar, low profile design with compact size of 100 × 50 mm². Thus, frequency agility, wide range tuning, compactness, and planar structure of the proposed antenna design make it suitable for modern wireless handheld devices particularly in cognitive radio applications.     

A frequency domain approach for parameter identification in multibody dynamics

The adjoint method shows an efficient way to incorporate inverse dynamics to engineering multibody applications, as, e.g., parameter identification. In case of the identification of parameters in oscillating multibody systems, a combination of Fourier analysis and the adjoint method is an obvious and promising approach. The present paper shows the adjoint method including adjoint Fourier coefficients for the parameter identification of the amplitude response of oscillations. Two examples show the potential and efficiency of the proposed method in multibody dynamics.     

A novel progressive modelling algorithm for 3D models

This paper presents a novel progressive modelling algorithm for 3D models to generate progressive meshes. We propose a forest clustering simplification method to generate a progressive mesh of a model with the efficient and smooth transitions between meshes at different resolutions. Our approach can also integrate and balance the appearance attributes to preserve features of a model in the simplification process. We have applied our progressive modelling technique to several different kinds of input models and results show that our approach only generates efficient and smooth progressive meshes of a given model, but also preserves the features. The proposed method is very suitable for progressive transmission and real‐time rendering of 3D models in networked virtual environments. Copyright © 2002 John Wiley & Sons, Ltd.     

一种适用于散射通信的联合帧同步和频偏估计算法研究

针对对流层散射通信中存在的多径衰落以及收发两端频偏,对一种适用于对流层散射通信的联合帧同步和频偏估计算法进行了研究;设计了一种适用于对流层散射通信的新型同步帧结构,其在帧同步信息前增加了周期循环PN序列用于辅助判决,能够提高衰落信道下的信号起点捕获概率;采用基于FFT的部分相关频域捕获算法,搜索最大相关值和频偏索引,同时完成了帧同步和频偏估计;在多径衰落和频偏影响下实现了联合帧同步和频偏估计算法;仿真结果表明:在衰落速率5 Hz,频偏1000 Hz散射信道下,正确捕获到帧同步信息概率在-4 dB信噪比下仍可达到90%以上,且频偏估计偏差在0.4 Hz以内     

A novel signal detection approach for fading channels with parameter statistics characteristics unknown

A novel signal detection approach is proposed in this paper. The approach exhibits the UMVUE of the probability density distribution function with respect to the received signal detection threshold value in wireless fading channels with unknown channel statistics characteristics. Multiscale particle filter is employed to extract the channel state information (CSI) from noisy observations available and to obtain a sufficient complete statistics of parameters. Based on the sufficient complete statistics, a conditional posterior probability density distribution for detection threshold value is derived via the Bayes statistic inference theorem in the presence of the additive white Gaussian noise (AWGN). Simulation results are given to illustrate the proposed novel scheme advantages.     

A novel video saliency estimation method in the compressed domain

Pattern Analysis and Applications - This paper presents a novel compressed domain saliency estimation method based on analyzing block motion vectors and transform residuals extracted from the...