Application of non-stationary signal characteristics using wavelet packet transformation

Although Fourier-based methods have been standard methods for frequency analysis, they are not well suited for the analysis of nonlinear or non-stationary systems due to their time-varying natures. Thus, in this paper, a wavelet packet-based technique, which calculates time-varying coherence functions for input/output relationships, is developed. The developed method uses the Coiflet wavelet that has been widely used in signal processing. It is applied to obtain the time-varying coherence function, and to detect the impulse signal from the impulse-embedded signal such as an automobile sound/vibration signal with an external impact caused by a collision or passing over rough terrain. Some characteristics of non-stationary behavior such as the wavelet packet coefficients, maximum phase plane (MPP) analysis and fault detection are also demonstrated. The method gives promising results of non-stationary input-output systems, and so may be used as an effective tool for condition monitoring or fault detection area. This paper was recommended for publication in revised form by Associate Editor Yeon June Kang Jae-Eung Oh received his B.S. degree of mechanical engineering at Hanyang University in 1975 and his M.S. degree of Safety Engineering at Yokohama National University in 1980. He then went on to receive his doctorate degree in environmental engineering from Tokyo Institute of Technology in 1983. He is currently the Vice President of KSNVE.     

混合IRS辅助大规模MISO中基于显性信道估计的联合波束成形设计

针对智能反射面辅助大规模MISO系统的波束成形设计,当前大多数研究都是基于信道状态信息完全已知,且未考虑基站端主动波束成形矩阵与智能反射面反射系数矩阵存在的耦合关系。智能反射面辅助的信道为级联信道,难以进行估计,且导频开销较大。鉴于此,采用了一种包含有源和无源元件的混合智能反射面架构,首先基于毫米波信道的稀疏特性,利用压缩感知算法估计信道,并设计一种融合注意力机制的两级卷积网络框架,以最大化和速率为目标,联合优化设计智能面反射系数矩阵和波束成形矩阵。实验结果表明,相比已有方法,所提方法可以使用更少的导频获得更优的和速率性能,有效减少了导频损耗,降低了计算时间复杂度。且当通信环境发生变化时,网络亦具有良好的鲁棒性。     

Blind recognition of STBC-OFDM signals based on modified K-S test

Aiming at the problem that existed blind classification of STBC-OFDM in multiple input single output (MISO) communication system,an efficient method for blind classification of space-time block coded orthogonal frequency-division multiplexing (STBC-OFDM) signals based on modified Kolmogorov-Smirnov (K-S) test was proposed,when a single receiver antenna was employed at the receiver.Firstly,the model of received STBC-OFDM signals in MISO systems was given.Secondly,with the correlation of the coding matrix of STBC-OFDM signals,and the discrimination features function provided by the empirical cumulative distribution (CDFs) of the received OFDM blocks was constructed.Finally,the distance between CDFs was tested by the two-sample K-S test,which could blindly classify the STBC-OFDM signals.The proposed algorithm didn't need the estimation of channel,noise statistics and modulation type,and consequently,was well suited for non-cooperative communication context.Theoretical analysis and experimental verify its validity.     

多波束机会波束成形系统性能比较

研究了在多输入单输出（MISO）系统中通过加大、加快信道的波动来提高多用户分集增益的机会波束成形技术,并在此基础上研究了在每个时隙中采用多个加权矢量的多波束机会波束成形技术,着重对它们的性能作了仿真比较。结果表明,多波束机会波束成形技术可以提高系统吞吐量。     

Neural models of solar collectors for prediction of daily performance

This paper presents the application of an online identification neural technique to the prediction of the in-situ daily performance of solar collectors. First, it is shown that the use of the Laplace transform helps to find the order of an approximated model; the input of the studied system being the solar radiation. Then it is shown that an NNOE model can be more accurate using the right size of the regression vector; the learning database consisting of the data obtained during half a day. Finally, it is shown that a multiple inputs single output (MISO) NNOE model can be accurate; the inputs being the solar radiation and the thermal heat loss conductance that depends on the wind velocity. In any case the differential between the actual value of the daily energy and the value computed by a neural model is less than 0.5%.     

基于矢量线性运算的自适应球帽差分反馈算法

信道时间相关多输入多输出(MIMO)系统中一种重要有限反馈策略为差分反馈,该文提出一种适用于单用户多输入单输出(SU-MISO)系统的自适应球帽差分反馈算法。首先,运用相邻时刻信道间的扰动规律设计自适应差分反馈策略;其次,不同于现有差分码本的非线性构造方法,提出一种基于矢量伸缩和合成的球帽差分码本算法;最后,联合球帽码本空间分布规律和时间相关信道的统计规律推导出球帽半径计算方法。仿真结果说明,该算法能准确跟踪信道并较现有算法有一定性能提高。     

多用户MISO系统下行链路的自适应用户选择算法

针对多用户多输入单输出(MISO)系统中的用户选择问题,该文基于多用户系统的容量公式提出一种低复杂度的自适应用户选择算法,使选择的用户数随当前的信道状态自适应变化以最大化所有用户的和速率。仿真结果表明,该算法具有接近最优的性能。在此基础上结合比例公平调度对算法进行改进以保证系统中用户服务的公平性。     

无线传感器网络中基于有限反馈的协同MIMO策略

该文针对无线传感器网络中能量有限问题,提出了一种基于有限反馈的协同MIMO策略。该策略基于梯度算法,用1bit反馈来自动地调整簇头节点和协同簇头节点的发射功率。对无线传感器网络中基于有限反馈的Alamouti码的协同MISO系统的误码率进行了理论分析,推导了基于有限反馈Alamouti码的协同MISO策略能耗的契尔诺夫上限表达式。理论分析和仿真结果都表明,该文提出的协同MISO策略与基于标准Alamouti码的协同策略相比,无线传感器网络的总能耗更低,能效更高,且当簇头节点和协同簇头节点一直选择较好信道对应的节点来发送信息时,即最优策略,无线传感器网络的总能耗更低。     

MISO current mode bi-quadratic filter employing high performance inverting second generation current conveyor circuit

This paper presents static and dynamic studies of a new CMOS realization for the inverting second generation current conveyor circuit (ICCII). The proposed design offers enhanced functionalities compared to ICCII circuits previously presented in the literature. It is characterized by a rail to rail dynamic range with high accuracy, a low parasitic resistor at terminal X (1.6 Ω) and low power consumption (0.31 mW) with wide current mode (3.32 GHz) and voltage mode (3.9 GHz) bandwidths.Furthermore, a new MISO current mode bi-quadratic filter based on using ICCII circuits as active elements is proposed. This filter can realize all standard filter responses without changing the circuit topology. It is characterized by active and passive sensitivities less than unity and an adjustment independently between pole frequency and quality factor. The operating frequency limit of this filter is about 0.8 GHz with 0.674 mW power consumption.The proposed current conveyor circuits and bi-quadratic filter are tested by TSPICE using CMOS 0.18 µm TSMC technology with ±0.8 V supply voltage to verify the theoretical results.