联合物理层与MAC层的multi-TRP上行重叠传输处理机制

针对非理想回程下现有协议难以有效处理多传输接收节点(multi-TRP)场景中多定时提前(multi-TA)导致的严重上行链路(UL)重叠传输问题,联合改进物理层复用技术和介质访问控制(MAC)令牌桶技术,提出了一种新型的UL重叠传输处理机制。该新型机制通过改进物理层重叠信道识别流程、复用要求及复用规则,将物理层复用信息与重叠信息反馈至MAC层,并对MAC层令牌桶技术进行优化。通过仿真实验对所提机制与现有协议机制进行对比,结果表明,在逻辑时隙不可重叠和可重叠2种情形下,物理上行控制信道(PUCCH)实际复用数量性能平均提升了57.58%和49.40%,物理上行共享信道(PUSCH)实际可用资源数量性能平均提升了12.09%和26.03%;优先级最高逻辑信道实际占用资源数量性能平均提升了33.33%和45.48%。

MCJ-UNet:一种双/多通道联合InSAR相位解缠网络

干涉合成孔径雷达(InSAR)可实现地表高程的高效获取,在地形测绘中应用广泛。双/多通道InSAR技术可借助不同通道(基线、频点)的高程模糊度差异,解决相位欠采样问题,完成高程陡变区域的干涉相位解缠,实现InSAR技术在测绘困难区域的有效应用。该文即面向高效高精度相位解缠需求,利用深度学习这一有力工具,结合不同通道的相位特征及相互约束关系,提出了一种双/多通道联合干涉相位解缠网络:Multi-Channel-Joint-UNet(MCJ-UNet)。该网络的构建以双通道(双频、双基线)InSAR为基本观测构型,并可实现向多通道构型的扩展,其构建的核心思路主要包括3点:首先,将干涉相位解缠中的模糊数估计问题转化为语义分割问题,并采用UNet网络完成分割处理;其次,引入挤压激励模块(SE)动态调整信息权重,以增强网络不同通道对其所需信息的感知能力;最后,利用多通道联合约束下的相位残差优化损失函数,实现网络调谐。此外,为避免语义分割结果的边缘细节误差对解缠效果的影响,该文还提出了一种基于多通道联合约束的解缠误差自修正方法,以保证解缠质量。模拟地形仿真数据、真实地形仿真数据以及TerraSAR-X实测数据验证了所提方法的有效性。

基于MSCAU-Net的视网膜眼底图像的硬渗出液分割

硬渗出液是早期糖尿病性视网膜病变(diabetic retinopathy,DR)的主要病症之一,在眼底图像中占据的像素点较少,其检测容易受视盘、软渗出液的干扰。针对这些问题,在U型网络(U-Net)结构的基础上,通过在编码器和解码器中融入残差模块和残差通道注意力模块学习硬渗出液的细微特征,在跳跃连接中加入一种新的多尺度通道注意力(multi-scale channel attention,MSCA)模块提升网络对稀疏小病灶的分割能力,提出了MSCA U-Net。基于超广角眼底图像数据集和印度糖尿病性视网膜病变图像数据集的实验结果表明,与其他基于卷积神经网络的图像分割方法相比,所提方法具有更高的硬渗出液分割精度。

基于Multi-Radio Multi-Channel传感器网络无冲突信道分配算法的研究

为降低通信冲突和信道干扰,对Mult-i Radio Mult-i Channel传感器网络无冲突信道进行研究,结果证实在网络通信半径大于3倍的网络最大功率通信半径的前提下,Sensor节点规模满足2倍网络功率级数加1的环境下,网络无冲突信道分配的信道数达到网络信道冲突图的最大值。文章通过对无冲突信道算法的运用,最终证实其可以有效地提高传感器网络的工作效率,大幅度提升网络的吞吐量。

基于Wi-Fi感知的多用户身份识别研究

随着无线感知技术的发展,基于Wi-Fi的身份识别研究在人机交互和家居安防等领域备受关注。尽管基于Wi-Fi信号的身份识别已经取得了初步的成功,但是目前主要适用于用户独立行为场景,并发行为下的多用户身份识别仍然面临着一系列挑战,包括用户之间的相互干扰以及模型鲁棒性差等问题。因此,提出了一种并发行为下多用户身份识别系统Wiblack,其核心思想是训练一个多分支深度神经网络(Wiblack-Net)来提取每个单用户的独特特征。首先,利用主干网络提取多用户之间的共同特征;然后,为每个用户分配一个二分类器以此判断给定群体中是否存在目标用户,在此基础上基于并发行为实现多个用户身份识别。此外,将Wiblack与多个独立的二分类模型和单个多分类模型进行对比实验,对运行效率和系统性能进行分析。实验结果显示,在同时识别3个用户身份时,Wibalck平均准确率达到了92.97%,平均精确度为93.71%,平均召回率为93.24%,平均F1值为92.43%。

基于RF与D-S证据理论融合的多通道齿轮箱复合故障诊断

针对齿轮箱复合故障特征难于提取,诊断缺乏自动识别性,且单通道往往无法全面表征故障信息等问题,提出一种基于随机森林与证据理论相融合的多通道齿轮箱复合故障诊断方法。首先通过小波包变换对各通道复合故障信号进行分解,得到故障信号的特征向量;之后引入一种新的特征集组合框架构建针对不同故障的特征数据集,通过随机森林算法划分单个分类模型;接着综合考虑各分类模型,合成每个通道下的集成分类器,并提出一种新的迭代自更新策略不断完善分类器的性能;最后设计一种基于Lance距离的改进D-S证据理论算法,该算法采用Lance距离来度量各空间证据间的证据距离,并构造Lance矩阵,由此获得相似度矩阵来衡量各证据体间的相似程度和支持度,通过计算各通道的敏感度权重系数进行BPA修正,获得最终的诊断融合结果。通过齿轮箱试验平台进行算法验证,结果表明该方法能有效识别出复合故障中包含的每类故障,并能全面融合不同通道的故障冗余信息,实现齿轮箱复合故障的精确诊断。

基于双模式分解多通道输入的VSC-STATCOM逆变器故障诊断模型

针对传统电压源型静止同步补偿器中逆变器故障诊断存在的信号特征提取不充分,深度学习网络识别能力不足以及高噪声情况下识别率较低等问题,提出了一种基于双模式分解、多通道输入(MCI)、并行卷积神经网络(PCNN)、双向长短时记忆(BiLSTM)网络和自注意力(SA)机制组合的逆变器故障诊断方法。首先利用变分模态分解和时变滤波经验模态分解对逆变器输出的三相电流进行分解,降低原始信号复杂程度,实现不同模态分量间的规律互补;其次,利用MCI-PCNN-BiLSTM-SA组合模型对特征矩阵进行深层特征提取、学习和识别;最后,通过仿真进行验证,结果表明所提方法特征提取能力较强,在无噪声情况下平均识别率高达99.48%,在高噪声情况下平均识别率达95.59%。

多通道平行流扁管-紧凑式翅片相变蓄热器蓄/放热性能

工业余热浪费严重、利用率较低且实际应用过程中受到时间和空间的限制,需要高效蓄热技术和装置来解决此类问题。提出一种将多通道平行流扁管与紧凑式翅片相结合的新型相变蓄热器,以水为载热流体,月桂酸为相变材料。实验研究了载热流体注入方式、流量、入口温度对蓄热器蓄/放热性能的影响,并分析小温差下蓄热器的传热特性。结果显示,该蓄热器相变材料填充率为82.5%,紧凑式翅片的采用极大强化了相变材料侧换热过程,蓄/放热性能优良。当载热流体入口温度分别为45℃和41℃时,相变材料约在270 min和75 min完成相变,最小蓄/放热温差可达2℃,最小温差时的平均蓄热比功率为25.18 W/kg,平均取热比功率为20.23 W/kg。

A Novel Design of Efficient Multi-channel UART Controller Based on FPGA

In traditional universal asynchronous receiver transmitter （UART） controller, the data transmission is inefficient and the data bus utilization ratio is low. A novel design is provided to solve these problems. The architecture of the system is introduced, the flow charts of data processing as well as the implementation state machine are also presented in detail. This paper is concluded by comparing the performance of this design, which is realized on field programmable gate army （FPGA） using Verilog hardware description language （HDL）, with other traditional UART controllers.

Performance analysis of multi-channel order statistics detector for range-spread target

The problem of two order statistics detection schemes for the detection of a spatially distributed target in white Gaussian noise are studied.When the number of strong scattering cells is known,we first show an optimal detector,which requires many processing channels.The structure of such optimal detector is complex.Therefore,a simpler quasi-optimal detector is then introduced.The quasi-optimal detector,called the strong scattering cells’ number dependent order statistics（SND-OS） detector,takes the form of an average of maximum strong scattering cells with a known number.If the number of strong scattering cells is unknown in real situation,the multi-channel order statistics（MC-OS） detector is used.In each channel,a various number of maximums scattered from target are averaged.Then,the false alarm probability analysis and thresholds sets for each channel are given,following the detection results presented by means of Monte Carlo simulation strategy based on simulated target model and three measured targets.In particular,the theoretical analysis and simulation results highlight that the MC-OS detector can efficiently detect range-spread targets in white Gaussian noise.

基于I-ConvNeXt的GAN生成人脸图像鉴别方法

为鉴别社交网络中人脸图像的真假,在ConvNeXt基础上提出一种针对生成式对抗网络(Generative Adversarial Networks,GAN)生成人脸图像的鉴别方法。该方法以ConvNeXt网络结构为主体,利用人脸图像的颜色特征和空间纹理特征,采用多颜色空间多通道组合输入(Multichannel Input,MCI),扩大网络的学习范围;同时引入通道注意力机制和空间注意力机制来凸显真假人脸图像在颜色分量和纹理特征上的差异,进而实现生成人脸图像和真实人脸图像的检测与识别。实验结果表明,使用改进后的ConvNeXt(Improved ConvNeXt,I-ConvNeXt)网络结构对GAN生成人脸图像的识别准确率达到了99.405%,与原ConvNeXt算法相比,平均准确率提高了1.455个百分点。该结果验证了所提方案的可行性、合理性。

基于电子舌结合VMD-IMG组合模型的清香型白酒掺假检测

针对传统白酒掺假检测方法分析流程长、仪器操作复杂等问题,提出一种基于电子舌结合变分模态分解和改进多通道GhostNet网络组合模型,实现对白酒掺假快速检测的方法。采用贝叶斯优化后的VMD对信号进行自适应模态分解,将原始信号分解为多个本征模态函数。在传统GhostNet网络的基础上,引入瓶颈注意力模块和空洞卷积,并扩展为多通道GhostNet,进而构建为VMD-IMG组合模型,以实现电子舌信号特征的有效提取和分类识别。试验结果表明,VMD-IMG组合模型具有较好的白酒掺假分辨性能,其测试的准确率、精确率、F1分数分别为98.33%,98.43%,98.34%。研究为白酒掺假检测提供一种快速、低成本的检测方法,并可为其他酒类或饮品掺假检测提供参考。

A time-sharing multi-channel pulse amplitude analyzer

A conventional multi-channel pulse amplitude analyzer acquires single energy spectrum,but provides no information on its tendency with time.To address the limitation,we propose a scheme of time-sharing multichannel pulse amplitude analyzer(TSMCA).A dual-port random access memory is divided into two storage spaces,one for current energy spectrum data acquisition and another for previous energy spectrum data storage.The two tasks can be performed simultaneously,and the time-related variation tendency of energy spectrum can be obtained.A prototype system of TSMCA is designed.It performs nicely,with maximum channel number of 4096 in capacity of 2^(32)/Ch,minimal time-sharing slice of 25 ms,the differential nonlinearity of <1.5%,and the integral nonlinearity of <0.3%.

Receding Horizon Estimation for Linear Discrete-time Systems with Multi-channel Observation Delays

This paper investigates the receding horizon state estimation for the linear discrete-time system with multi-channel observation delays. The receding horizon estimation is designed by the reorganized observation technique and the linear unbiased estimation method. The estimation gains are developed by solving a set of Riccati equations, and a stability result about the state estimation is shown. Finally, an example is given to illustrate the efficiency of the receding horizon state estimation.

A Multi-Gap Multi-Channel Gas Switch for the Linear Transformer Driver

A multi-gap and multi-channel gas switch with convexo-convex discal planet electrodes was designed and investigated. Eight gaps are formed in series by a trigger electrode, six intermediate electrodes and two high voltage electrodes with a uniform gap length of 5 ram. The self breakdown and triggered breakdown performance of the switch are reported. Both the delay time and jitter decrease with the increase in the trigger voltage, switching coefficient and the decrease in the trigger isolating resistor. The delay time of the switch is about 40 ns, and the jitter is less than 2 ns when charged with 4-85 kV and triggered by a voltage pule of -75 kV. The inductance of the switch is about 30 nH.

Multi-channel 28-GHz millimeter-wave signal generation on a silicon photonic chip with automated polarization control

We propose and experimentally demonstrate an integrated silicon photonic scheme to generate multi-channel millimeter-wave(MMW) signals for 5 G multi-user applications. The fabricated silicon photonic chip has a footprint of 1.1 × 2.1 mm^2 and integrates 7 independent channels each having on-chip polarization control and heterodyne mixing functions. 7 channels of4-Gb/s QPSK baseband signals are delivered via a 2-km multi-core fiber(MCF) and coupled into the chip with a local oscillator(LO) light. The polarization state of each signal light is automatically adjusted and aligned with that of the LO light, and then 7 channels of 28-GHz MMW carrying 4-Gb/s QPSK signals are generated by optical heterodyne beating. Automated polarizationcontrol function of each channel is also demonstrated with ～7-ms tuning time and ～27-dB extinction ratio.

Joint channel assignment and cross-layer routing protocol for multi-radio multi-channel Ad Hoc networks

To study multi-radio multi-channel （MR-MC） Ad Hoc networks based on 802.11, an efficient cross-layer routing protocol with the function of joint channel assignment, called joint channel assignment and cross-layer routing （JCACR）, is presented. Firstly, this paper introduces a new concept called channel utilization percentage （CUP）, which is for measuring the contention level of different channels in a node’s neighborhood, and deduces its optimal value for determining whether a channel is overloaded or not. Then, a metric parameter named channel selection metric （CSM） is designed, which actually reffects not only the channel status but also corresponding node’s capacity to seize it. JCACR evaluates channel assignment by CSM, performs a local optimization by assigning each node a channel with the smaller CSM value, and changes the working channel dynamically when the channel is overloaded. Therefore, the network load balancing can be achieved. In addition, simulation shows that, when compared with the protocol of weighted cumulative expected transfer time （WCETT）, the new protocol can improve the network throughput and reduce the end-to-end average delay with fewer overheads.

Cutaneous sensory nerve as a substitute for auditory nerve in solving deaf-mutes' hearing problem: an innovation in multi-channel-array skin-hearing technology

The current use of hearing aids and artificial cochleas for deaf-mute individuals depends on their auditory nerve. Skin-hearing technology, a patented system developed by our group, uses a cutaneous sensory nerve to substitute for the auditory nerve to help deaf-mutes to hear sound. This paper introduces a new solution, multi-channel-array skin-hearing technology, to solve the problem of speech discrimination. Based on the filtering principle of hair cells, external voice sig- nals at different frequencies are converted to current signals at corresponding frequencies using electronic multi-channel bandpass filtering technology. Different positions on the skin can be stimulated by the electrode array, allowing the perception and discrimination of external speech signals to be determined by the skin response to the current signals. Through voice frequen- cy analysis, the frequency range of the band-pass filter can also be determined. These findings demonstrate that the sensory nerves in the skin can help to transfer the voice signal and to dis- tinguish the speech signal, suggesting that the skin sensory nerves are good candidates for the replacement of the auditory nerve in addressing deaf-mutes＇ hearing problems. Scientific hearing experiments can be more safely performed on the skin. Compared with the artificial cochlea, multi-channel-array skin-hearing aids have lower operation risk in use, are cheaper and are more easily popularized.

A multi-channel chemical sensor and its application in detecting hydrothermal vents

There are well-established chemical and turbidity anomalies in the plumes occurring vicinity of hydrothermal vents, which are used to indicate their existence and locations. We here develop a small, accurate multi-channel chemical sensor to detect such anomalies which can be used in deep-sea at depths of more than 4 000 m. The design allowed five all-solid-state electrodes to be mounted on it and each (apart from one reference electrode) could be changed according to chemicals to be measured. Two experiments were conducted using the chemical sensors. The first was a shallow-sea trial which included sample measurements and in situ monitoring. pH, Eh, CO3^2- and SO4^2- electrodes were utilized to demonstrate that the chemical sensor was accurate and stable outside the laboratory. In the second experiment, the chemical sensor was integrated with pH, Eh, CO3^2- and H2S electrodes, and was used in 29 scans of the seabed along the Southwest Indian Ridge (SWIR) to detect hydrothermal vents, from which 27 sets of valid data were obtained. Hydrothermal vents were identified by analyzing the chemical anomalies, the primary judging criteria were decreasing voltages of Eh and H2S, matched by increasing voltages of pH and CO3^2- . We proposed that simultaneous detection of changes in these parameters will indicate a hydrothermal vent. Amongst the 27 valid sets of data, five potential hydrothermal vents were targeted using the proposed method. We suggest that our sensors could be widely employed by marine scientists.

Design and Implementation of a High-Speed Multi-Channel Data Acquisition System

A data acquisition system （DAS） to implement high-speed, real-time and multi-channel data acquisition and store is presented. The control of the system is implemented by the combination of complex programable logic device （CPLD） and digital signal processing （DSP）, the bulk buffer of the system is implemented by the combination of CPLD, DSP, and synchronous dynamic random access memory （SDRAM）, and the data transfer is implemented by the combination of DSP, first in first out （FIFO）, universal serial bus （USB） and USB hub. The system could not only work independently in single-channel mode, but also implement high-speed real-time multi-channel data acquisition system （MCDAS） by the combination of multiple single-channels. The sampling rate and data storage capacity of each channel could reach up to 100 million sampiing per second and 256 MB respectively.