Factor-graph-based iterative channel estimation and signal detection algorithm over time-varying frequency-selective fading channels

The problem of soft-input so,output （ SISO ） detection for time-varying frequency-selec- tive fading channels is considered. Based on a suitably-designed factor graph and the sum-product al- gorithm, a low-complexity iterative message passing scheme is proposed for joint channel estima- tion, equalization and decoding. Two kinds of schedules （parallel and serial） are adopted in message updates to produce two algorithms with different latency. The computational complexity per iteration of the proposed algorithms grows only linearly with the channel length, which is a significantly de- crease compared to the optimal maximum a posteriori （MAP） detection with the exponential com- plexity. Computer simulations demonstrate the effectiveness of the proposed schemes in terms of bit error rate performance.

Spacetime coded eigenbeamforming for downlink frequency-selective correlated fading channels

To improve the performance of space-time coding over downlink frequency-selective correlated fading channels, a novel transmission scheme combining eigenbeamfoming and OFDM is proposed. Provided that the channel correlated statistics are available at the transmitter, the wideband correlated fading channels can be converted into an independent FIR channel with 2 transmitting antennas and N receiving antennas by eigenbeamforming and dimension reduction. OFDM is utilized to convert the FIR channel into a group of independent parallel subchanneis to carry space-time codes. With the new structure, the performance of space-time coding over downlink wideband correlated fading channels is greatly improved and the system complexity is reduced. Validity of the proposed system is verified by simulations under different conditions. Comparison between the new structure and an available structure is made both theoretically and computationslly.

A Deep Learning Based Broadcast Approach for Image Semantic Communication over Fading Channels

We consider an image semantic communication system in a time-varying fading Gaussian MIMO channel,with a finite number of channel states.A deep learning-aided broadcast approach scheme is proposed to benefit the adaptive semantic transmission in terms of different channel states.We combine the classic broadcast approach with the image transformer to implement this adaptive joint source and channel coding(JSCC)scheme.Specifically,we utilize the neural network(NN)to jointly optimize the hierarchical image compression and superposition code mapping within this scheme.The learned transformers and codebooks allow recovering of the image with an adaptive quality and low error rate at the receiver side,in each channel state.The simulation results exhibit our proposed scheme can dynamically adapt the coding to the current channel state and outperform some existing intelligent schemes with the fixed coding block.

Effective Capacity of URLLC over Parallel Fading Channels with Imperfect Channel State Information

This paper investigates the effective capacity of a point-to-point ultra-reliable low latency communication(URLLC)transmission over multiple parallel sub-channels at finite blocklength(FBL)with imperfect channel state information(CSI).Based on reasonable assumptions and approximations,we derive the effective capacity as a function of the pilot length,decoding error probability,transmit power and the sub-channel number.Then we reveal significant impact of the above parameters on the effective capacity.A closed-form lower bound of the effective capacity is derived and an alternating optimization based algorithm is proposed to find the optimal pilot length and decoding error probability.Simulation results validate our theoretical analysis and show that the closedform lower bound is very tight.In addition,through the simulations of the optimized effective capacity,insights for pilot length and decoding error probability optimization are provided to evaluate the optimal parameters in realistic systems.

Symbols detection for frequency-selective V-BLAST OFDM systems

As the combining form of the orthogonal frequency-division multiplexing (OFDM) technique and the vertical Bell Labs layered space-time (V-BLAST) architecture, the V-BLAST OFDM system can better meet the demand of next-generation (NextG) broadband mobile wireless multimedia communications. The symbols detection problem of the V-BLAST OFDM system is investigated under the frequency-selective fading environment. The joint space-frequency demultiplexing operation is proposed in the V-BLAST OFDM system. Successively, one novel half-rate rotational invariance joint space-frequency coding scheme for the V-BLAST OFDM system is proposed. By elegantly exploiting the above rotational invariance property, we derive one direct symbols detection scheme without knowing channels state information (CSI) for the frequency-selective V-BLAST OFDM system. Extensive simulation results demonstrate the validity of the novel half-rate rotational invariance joint space-frequency coding scheme and the performance of the direct symbols detection scheme.

The research of high-directive anisotropic magnetic metamaterial antenna loaded with frequency-selective surface

This paper uses a Computer Simulation Technology microwave studio to simulate the performance of a new highdirectivity anisotropic magnetic metamaterial antenna loaded with a frequency-selective surface. Frequency-selective surface with cross-dipole element has a great effect on the directivity, radiation pattern, and gain of such an antenna. The experimental results show that frequency-selective surface （FSS） significantly improve the radiation performance of anisotropic magnetic metamaterial antenna. For example, as a single anisotropic magnetic metamaterial antenna, half power beam width is 4 degrees in the H planes, and the gain of this antenna is 19.5dBi at 10CHz, achieving a 2.1 degree increment in half power beam width, and a 7.3 dB gain increment by loading with the FSS reflector. The simulating results are consistent with our experimental results.

Frequency-selective attenuation of sound propagation and reverberation in shallow water

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The effect of a non-aligned unit on double-screen frequency-selective surface transmission characteristics

Double-screen frequency-selective surfaces （FSSs） can bring about a better flattened effect and a rapidly declining edge. They are therefore an effective means to achieve outer-zone stealth of the radar cabin to detect radar waves. In this article, a double-screen wide-bandpass FSS structure is designed and the transmission characteristics of the units under alignment and non-alignment are simulated by means of the spectral domain approach. Meanwhile, the experimental parts fabricated by vacuum evaporation and lithography are tested in a microwave chamber. Tile results show that the aligned unit structure has good incident angle stability and can achieve high transmittance when the bandwidth is 3.3 GHz, and the transmission loss is less than -1 dB. When the units have a non-aligned structure, the bandwidth decreases and transmission loss increases with increasing incident angle.

Design of double-layer active frequency-selective surface with PIN diodes for stealth radome

An experimental double-layer active frequency-selective surface（AFSS） for stealth radome is proposed. The AFSS is a planar structure which is composed of a fixed frequency-selective surface（FSS）, a PIN diodes array, and a DC bias network. The AFSS elements incorporating switchable PIN diodes are discussed. By means of controlling the DC bias network, it is possible to switch the frequency response for reflecting and transmitting. Measured and simulated data validate that when the incidence angle varies from 0°to 30° the AFSS produces more than-11.5 dB isolation across6–18 GHz when forward biased. The insertion loss（IL） is less than 0.5 dB across 10–11 GHz when reverse biased.

Optimizing Power Allocation for D2D Communication with URLLC under Rician Fading Channel:A Learning-to-Optimize Approach

To meet the high-performance requirements of fifth-generation(5G)and sixth-generation(6G)wireless networks,in particular,ultra-reliable and low-latency communication(URLLC)is considered to be one of the most important communication scenarios in a wireless network.In this paper,we consider the effects of the Rician fading channel on the performance of cooperative device-to-device(D2D)communication with URLLC.For better performance,we maximize and examine the system’s minimal rate of D2D communication.Due to the interference in D2D communication,the problem of maximizing the minimum rate becomes non-convex and difficult to solve.To solve this problem,a learning-to-optimize-based algorithm is proposed to find the optimal power allocation.The conventional branch and bound(BB)algorithm are used to learn the optimal pruning policy with supervised learning.Ensemble learning is used to train the multiple classifiers.To address the imbalanced problem,we used the supervised undersampling technique.Comparisons are made with the conventional BB algorithm and the heuristic algorithm.The outcome of the simulation demonstrates a notable performance improvement in power consumption.The proposed algorithm has significantly low computational complexity and runs faster as compared to the conventional BB algorithm and a heuristic algorithm.

Secure Wireless Multicasting through Nakagami-m Fading Channels with Multi-Hop Relaying

The additional diversity gain provided by the relays improves the secrecy capacity of communications system significantly. The multiple hops in the relaying system is an important technique to improve this diversity gain. The development of an analytical mathematical model of ensuring security in multicasting through fading channels incorporating this benefit of multi-hop relaying is still an open problem. Motivated by this issue, this paper considers a secure wireless multicasting scenario employing multi-hop relaying technique over frequency selective Nakagami-m fading channel and develops an analytical mathematical model to ensure the security against multiple eavesdroppers. This mathematical model has been developed based on the closed-form analytical expressions of the probability of non-zero secrecy multicast capacity (PNSMC) and the secure outage probability for multicasting (SOPM) to ensure the security in the presence of multiple eavesdroppers. Moreover, the effects of the fading parameter of multicast channel, the number of hops and eavesdropper are investigated. The results show that the security in multicasting through Nakagami-m fading channel with multi-hop relaying system is more sensitive to the number of hops and eavesdroppers. The fading of multicast channel helps to improve the secrecy multicast capacity and is not the enemy of security in multicasting.

IRS辅助的车联网相移设计和信道对齐策略

针对车联网中车辆的动态移动以及信号的随机散射所导致的信道快速变化问题,研究了智能反射面(intelligent reflecting surface,IRS)辅助的车联网通信并提出了联合相移设计和信道对齐策略,以削减车联网中多普勒频移的影响并提升通信性能。提出的策略由两个阶段构成。在第一阶段设计IRS的相移以改善级联信道的衰落状态,在策略的第二阶段进行修正函数的设计,实现了直接信道和级联信道的信道对齐,从而减少直接信道快衰落状态对通信性能的影响。通过联合相移设计和信道对齐策略中设计的反射相移以及修正函数,实现了通信性能的提升。仿真结果表明,所提策略相比于相移优化策略可以提升8.8%的频谱效率。

基于代谢组和转录组的银缕梅叶片退红机制初探

为了探究银缕梅〔Parrotia subaequalis(H.T.Chang)R.M.Hao et H.T.Wei〕叶片在春季由红转绿的物质基础和分子机制,采用代谢组和转录组联合分析对银缕梅幼叶和成熟叶中差异花色苷类成分含量及差异表达基因进行比较分析,并对花色苷合成关键酶基因进行生物信息学分析。结果表明:幼叶中花色苷类成分的总相对含量约为成熟叶的27倍;幼叶中锦葵色素3-O-葡萄糖苷、锦葵色素3-O-半乳糖苷和芍药花素3-O-葡萄糖苷的相对含量明显高于其他花色苷类成分,且极显著(p<0.01)高于成熟叶中对应成分的相对含量。比较幼叶和成熟叶的转录组数据,共筛选出11000个差异表达基因。GO功能富集结果显示富集到催化活性的差异表达基因最多(3000个);KEGG富集分析结果显示差异表达基因显著富集在植物激素信号转导通路和苯丙烷生物合成通路。通过与葡萄(Vitis vinifera Linn.)中已知的花色苷合成关键酶氨基酸序列进行比对,共筛选出9个银缕梅花色苷合成酶基因,并且这9个基因在幼叶中的相对表达量明显高于成熟叶。qRT-PCR结果表明:PsCHS1、PsF3′H、Ps3GT和PsAOMT的相对表达量极显著高于成熟叶。PsCHS1、PsF3′H、Ps3GT和PsAOMT分别包含393、528、461和323个氨基酸残基;4个蛋白的二级结构均以α螺旋和无规卷曲为主,其中,PsF3′H不含β转角,其余3个蛋白均由α螺旋、β转角、延伸链和无规卷曲构成;4个蛋白的三级结构均含有相应蛋白家族的保守结构。系统进化树显示:PsCHS1与红花檵木(Loropetalum chinense var.rubrum Yieh)的LcCHS,PsF3′H与枫香树(Liquidambar formosana Hance)的LfF3′H,Ps3GT与可可(Theobroma cacao Linn.)的Tc3GT,以及PsAOMT与枫香树的LfAOMT分别首先聚在一起。综上所述,锦葵色素3-O-葡萄糖苷、锦葵色素3-O-半乳糖苷和芍药花素3-O-葡萄糖苷可能是银缕梅叶片退红的主效花色苷类成分,PsCHS1、PsF3′H、Ps3GT和PsAOMT可能是银缕梅叶片退红的关键基因。

无线光通信中大气湍流噪声测量研究

光信号的强度闪烁、光斑漂移、光束扩展、到达角起伏等大气湍流现象会影响光信号在大气中的传输性能。本文将这种闪烁效应看作是光通信系统传输中的乘性噪声,推导了大气湍流乘性噪声模型,并进行了实验测量研究。结果表明:按照晴天、雾霾天、雪天、小雨天、中雨天、大雨天及阴天的顺序,湍流乘性噪声对光通信的通信质量影响加剧,大气折射率结构常数逐渐增大,噪声信号的偏斜度与陡峭度随之增加,导致光强信号的衰落概率变大;同时随着信噪比(signal-to-noise ratio,SNR)的增大,系统的中断概率逐渐减小;而在相同的SNR下,中断概率随着大气折射率结构常数的减小而减小。研究大气湍流噪声对无线光通信系统的影响具有重要的意义,它为大范围、高速的无线光通信技术带来重要的技术突破,对无线光通信技术的发展起到重要的作用。

无界域上具有记忆的非自治Plate方程随机吸引子的存在性

研究无界域上一类具有衰退记忆和加性噪声的非自治Plate方程解的长时间行为.利用一致估计验证了解的拉回渐近紧性,获得了其随机吸引子的存在性.

基于双参考优化的壁画图像色彩还原

褪变色壁画图像的色彩还原研究可以促进壁画的保护和展示。壁画图像色彩还原旨在将退化壁画图像的色彩褪变区域还原为原有色彩。常规的基于单幅参考壁画图像的色彩还原方法难以选取与退化壁画图像相似的参考壁画图像,进而影响色彩还原质量。为此,提出一种基于双参考优化的壁画图像色彩还原方法。采用双参考策略,即使用2幅参考壁画图像对退化壁画图像进行色彩还原,利用图像优化模块抑制褪变色壁画图像中普遍存在的噪声、划痕等多重退化,通过编码器-解码器网络编码提取壁画图像多尺度特征,并构建特征融合模块优化壁画图像的多尺度特征。采用双参考指导模块计算参考壁画图像与退化壁画图像的语义对应置信度,以实现图像区域间的相似性匹配,并实现2幅参考壁画图像的风格融合。在此基础上,利用融合特征实现退化壁画图像的色彩还原。实验结果表明,该方法可以较准确地还原退化壁画图像色彩,同时能较好保持壁画图像原有的边缘结构信息,并且使用无参考图像质量评估指标对各个方法的还原壁画图像进行客观评估,与对比方法相比,该方法在客观评估指标上最多可降低12.2%。

高原地区VHF地空通信覆盖范围影响因素研究

针对利用地形遮蔽法计算的民航VHF通信信号覆盖范围较粗略的问题,提出了一种在原有的算法下加入雾衰减从而提高信号覆盖精度的算法模型,并构建可视化的显示平台。首先,以西藏某高原地区VHF通信监视台站为例,利用地理信息系统从实际的地图中获取台站周围的数字高程模型(DEM),计算在地形影响下不同高度层上的信号传播截止距离;其次,根据国际电联无线电通信部门(ITU-R)P系列建议书中的雾衰减模型,构造在地形和雾共同影响下的新算法模型;最后,给定飞行高度、发射频率、发射功率等进行仿真。结果表明,多因素影响下的信号覆盖范围比单因素下的覆盖范围精确,可以为VHF地面通信监视台站选址、飞行航线规划以及西部地区民航发展提供有效支撑。

SUBDIVISION建模在室内有机形态的应用研究

通过探索Subdivision建模技术在室内设计中的潜力,提高室内设计有机形态的吸引力和竞争力,并且有效提高设计师在有机形态设计中的效率。通过分析Subdivision建模原理,介绍其在室内运用的可能性、高效性、调节性、仿生性的特点。对其Subdivision建模在室内设计应用中的有机拓扑形态、空间界面软化、泰森多边形应用、渐消面的运用等几点优势展开讨论。结合乐嘉伦敦展厅和BarinSkiResort、Batwings案例,阐述其非线性美学和有机形态,解读其设计特点。进一步分析Subdivision建模的有机形态表达优势与局限性,探讨Subdivision建模在室内设计中的有机结构建模的可行性。探析出Subdivision建模技术能够更好设计具有非线性美学的有机形态,更有助于创造出独特的艺术形式和空间感受。为相关室内空间有机形态的设计提供了创新的设计思路。

车联网V2I场景下基于GNN的SC-FDMA智能信道估计

随着车联网的迅猛发展,车对路基础设施(Vehicle to Infrastructure,V2I)通信对车联网的可靠性和时延提出了更高的要求,而信道估计是接收机高可靠低时延通信的重要保障.为解决传统信道插值算法不能有效拟合V2I信道快时变特性、自适应多普勒频移能力弱和传统神经网络可解释性不强的问题,本文提出基于图神经网络(Graph Neural Network,GNN)的单载波频分多址(Single Carrier-Frequency Division Multiple Access,SC-FDMA)智能信道估计算法.该算法将信道频率响应中的数据点作为图的节点、符号间时域相关性作为边,将图化后的数据送入GraphSAGE信道插值器(GraphSAGE Channel Interpolator,GCI)中,通过边更新、聚合操作、节点更新三大模块进行网络训练,同时采用多普勒频移矢量作为节点特征控制网络拟合不同多普勒条件的信道,使得网络具备可解释性.最后,系统仿真验证了在不同速度环境下算法的有效性和鲁棒性,较线性插值、样条插值以及全连接网络,本文所提GCI在低、中和高速移动环境下具有最优的误码率(Bit Error Rate,BER)和归一化均方误差(Normalized Mean Square Error,NMSE)性能,特别地,在200 km/h高速移动条件下GCI的优势更为明显.

基于莱斯信道的大规模MIMO协作中继网络设计与优化

随着移动通信技术的不断发展,大规模多输入多输出(Multiple Input Multiple Output,MIMO)系统被广泛应用于提高网络容量和性能。而协作中继网络作为一种有效提高通信覆盖能力和网络容量的手段,也受到越来越多的关注。文章基于莱斯信道模型,针对大规模MIMO协作中继网络进行设计与优化,旨在提升网络的可靠性和传输效率。通过对信道特性的分析和系统参数的优化,可以实现更好的性能表现。