Low-complexity transceiver design scheme based on channel null-space feedback

To reduce the negative impact of channel quantization errors, a low-complexity transceiver joint design scheme for both the transmit beamformers and receive combining vectors is proposed in the two-user multiple-input multiple-output （MIMO） system. In the scheme, the channel nullspace quantization vector is used as the transmit beamformer of the interference user directly based on channel null-space feedback. Since the interference can be determined at the receiver, interference rejection combining （IRC） is jointly utilized to cancel the inter-user interference. Simulation re- sults show that the proposed scheme can provide substantial sum-rate improvement especially at high SNR.

2-D RAKE RECEIVER BASED ON SPACE-TIME CHANNEL PARAMETER ESTIMATION

2-D RAKE receiver is an efficient way to realize the space-time processing for CDMA systems with aperiodic spreading codes. The Direction Of Arrival (DOA) and the relative time delay of every user's multipath must be known to realize the 2-D RAKE receiver. In the third generation CDMA mobile communication system, auxiliary pilot channel is used in the uplink channels The different user's Vector Channel Impulse Response (VCIR) can be estimated from the pilotichannel easily. The VCIR contains spatial and temporal information. In this paper,by utilizing the known pulse shape function, a parameter matrix method used to estimate the Spatial Signature Vector (SSV) and the relative time delay is proposed in frequency domain.The DOA can be estimated from the SSV. By reconstructing the SSV and utilizing approximate Capon space filter, the performance of the 2-D RAKE receiver with uniform circular array can be improved with a little additional computation work.

A new layered space-time detection algorithm for frequency selective fading multiple-input multiple-output channels based on particle filter

In this paper, a new observation equation of non-Gaussian frequency selective fading Bell Labs layered space time （BLAST） architecture system is proposed, which is used for frequency selective fading channels and non-Gaussian noise in an application environment of BLAST system. With othogonal matrix triangularization （QR decomposition） of the channel matrix, the static observation equation of frequency selective fading BLAST system is transformed into a dynamic state space model, and then the particle filter is used for space-time layered detection. Making the full use of the finite alphabet of the digital modulation communication signal, the optimal proposal distribution can be chosen to produce particle and update the weight. Incorporated with current method of reducing error propagation, a new space-time layered detection algorithm is proposed. Simulation result shows the validity of the proposed algorithm.

Channel Coding at Finite Blocklength and Its Application in 6G URLLC

To support mission-critical applications, such as factory automation and autonomous driving, the ultra-reliable low latency communications (URLLC) is adopted in the fifth generation (5G) mobile communications network, which requires high level of reliability and low latency. Naturally, URLLC in the future 6G is expected to have a better capability than its 5G version which poses an unprecedented challenge to us. Fortunately, the potential solution can still be found in the well-known classical Shannon information theory. Since the latency constraint can be represented equivalently by blocklength, channel coding at finite blocklength plays an important role in the theoretic analysis of URLLC. Applying these achievements in rapidly development of massive MIMO techniques gives rise to a new theory on space time exchanging. It tells us that channel coding can also be performed in space domain, since it is capable of providing the same coding rate as that in time domain. This space time exchanging theory points out an exciting and feasible direction for us to further reduce latency in 6G URLLC. .

OTFS系统SBL-Turbo压缩感知信道估计算法

针对正交时频空调制(OTFS)系统由多普勒频移引起的信道估计准确度下降的问题,本文提出了一种联合无线信道在时延-多普勒域稀疏特性的SBL-Turbo压缩感知信道估计算法。首先,对时延-多普勒域稀疏信道建模,使其服从以噪声功率为条件的高斯先验分布,利用稀疏贝叶斯学习模块估计得到稀疏信道的均值与方差,并结合期望最大化算法更新高斯先验模型中的参数。其次,引入了LMMSE(线性最小均方误差)估计器模块,该模块对稀疏信道的后验分布进行再估计,提高估计的准确度。通过对每个模块估计得到的信道后验分布进行数据处理,使得模块的输入值与输出值解耦,进而减少模块间的错误传播。最后,两个模块采用Turbo结构迭代估计信道的后验分布,得到信道状态信息。实验结果表明,相较于其他估计方法,该算法能够显著提高信道估计的精度,并且改善系统的误码率性能,能够有效地解决OTFS系统中由多普勒频移引起的信道估计问题。

Performance Analysis of AF Relaying Aided Space Shift Keying System with Imperfect Channel Estimation

Space shift keying (SSK) is a spectrally efficient and low-complexity technique that only uses antenna index to convey information.Combining SSK with cooperative communication,the transmission reliability of SSK system can be improved effectively.In this paper,considering imperfect channel information,the performance of cooperative SSK system with amplify-and-forward (AF) relaying protocol is investigated,and the effect of estimation error on the performance is analyzed.According to the performance analysis,the probability density function and moment generating function of effective signal-to-noise ratio are derived,respectively.Using these results,the closed-form expression of average bit error rate (BER) can be achieved.Meanwhile,the asymptotically approximated BER and the corresponding diversity order analysis are presented for the performance evaluation.By computer simulations,the validness of the presented theoretical analysis is verified,and the theoretical BERs with different estimation errors are shown to be close to those of the corresponding simulations.

Joint channel estimation and symbol detection for space-time block code

The simplified joint channel estimation and symbol detection based on the EM (expectation-maximization) algorithm for space-time block code (STBC) are proposed. By assuming channel to be invariant within only one STBC word and utilizing the orthogonal structure of STBC, the computational complexity and cost of this algorithm are both very low, so it is very suitable to implementation in real systems.

Power control scheme for multiple antenna systems with space-time coding in Rayleigh fading channels

Two optimal power control （PC） schemes under the power constraint for space-time coded multiple input multiple output systems over the flat Rayleigh fading channel with the imperfect channel state information （CSI） are presented. One is based on the minimization of a bit error rate （BER）, and the other is based on the maximization of a fuzzy signal-to-noise ratio. In these schemes, different powers are allocated to individual transmit an- tennas rather than equal power in the conventional one. For the first scheme, the optimal PC procedure is developed. It is shown that the Lagrange multiplier for the constrained optimization in the power control does exist and is unique. A practical iterative algorithm based on Newton＇s method for finding the Lagrange multiplier is proposed. In the second scheme, some existing schemes are included, and a suboptimal PC procedure is developed by means of the asymptotic performance analysis. With this suboptimal scheme, a simple PC calculation formula is provided, and thus the calculation of the PC will be straightforward. Moreover, the suboptimal scheme has the BER performance close to the optimal scheme. Simulation results show that the two PC schemes can provide BER lower than the equal PC and antenna selection scheme under the imperfect CSI.

一种低复杂度的正交时频空系统接收机设计

正交时频空(OTFS)调制可以将时间和频率选择性信道转换为时延-多普勒(DD)域的非选择性信道,这为高速移动场景建立可靠的无线通信提供了解决方案。然而,在车联网等复杂的多散射场景下,信道存在严重的多普勒间干扰(IDI),这给OTFS接收机信号的准确解调带来了极大的挑战。针对上述问题,该文提出一种联合稀疏贝叶斯学习(SBL)和阻尼最小二乘最小残差(d-LSMR)的OTFS接收机设计。首先,根据OTFS时域和DD域的关系,采用基扩展模型(BEM)将信道估计问题转换为基系数恢复问题,精准估计包括多普勒采样点在内的DD域信道。然后,提出一种高效的转换算法将基系数转换为信道等效矩阵。其次,将信道估计中估计得到的噪声,用于d-LSMR均衡器中进行信道均衡,并利用DD域信道矩阵的稀疏性实现快速收敛。系统仿真结果表明,与目前代表性的OTFS接收机相比,该文所提方案实现了更好的误码率性能,同时降低了计算复杂度。

利用元学习算法的IRS-OTFS通信系统信道估计

针对高多普勒场景下智能反射表面(IRS)辅助多用户通信系统存在的信道估计传输开销大的问题,该文结合正交时频空间(OTFS)调制特点构造一种IRS-OTFS通信系统,充分发挥IRS和OTFS的性能优势,并在此基础上提出一种学习率自适应的模型无关元学习(MAML)算法。对IRS-OTFS多用户信道估计任务做离线训练,根据各任务的收敛速度自适应地调整学习率,防止训练失衡,并利用信道之间的相关性和MAML算法的少样本、泛化特性得到全局模型和适应性模型,快速学习新用户信道的传输特性,降低传输开销,提高信道估计准确性。理论分析和仿真结果表明,该算法在信道传输条件相同的情况下,将传输开销降低了大约50%,并相对于基准算法有4.8 dB左右的性能提升。

基于机器学习的OTFS系统信道估计与信号检测研究进展

OTFS调制可以在高速移动场景下有效对抗ICI,能提供比传统的OFDM更显著的性能增益,充分提升高多普勒扩展场景下的通信系统频谱效率,改善通信系统质量,近年来得到广泛研究。OTFS系统的研究重点和难点在于信道估计与信号检测。人工智能已经成为一种有效的信息处理手段,在各行业都得到了广泛的应用。而机器学习是人工智能中的重要分支,通过将机器学习与OTFS技术相结合,可以有效解决信道估计与信号检测中的问题,提高系统性能、稳定性和可靠性。对目前基于机器学习的OTFS系统的信道估计与信号检测算法进行了较为全面的调研、分析、对比和归纳,进而梳理出技术挑战,并就未来的技术发展趋势进行了探讨。

利用瑞利面波提高近地表横波速度精度的方法

二维油气地震勘探中,由于受野外施工条件、成本效益等诸多因素限制,地震记录的野外采集道间距往往较大,这种地震记录往往容易产生空间假频,降低其频率—速度谱信噪比。为此,提出利用小波变换良好的时频分析特性,对大时空采样记录进行基于小波基的道内插值,以提高P-SV转换波地震资料中的瑞利面波频散高频信息的精度,从而提高反演表层横波速度结构精度,提高P-SV转换波的横波静校正精度。对理论模型和实际数据进行的验证计算表明,基于小波基的道内插值方法具有抗假频性,瑞利面波基阶频散曲线拐点更清晰,高频段能量更加集中,反演的横波速度精度更高,取得了较好效果。

干旱地区河槽暗蓄雨洪资源化利用模拟

目的 研究利用雨洪资源解决干旱地区用水短缺问题,提出利用河槽暗蓄收集雨洪最佳工程方案,为该类工程的设计提供参考。方法 应用Visual Modflow软件模拟研究辽西喀左地区内第二牤牛河流域中不同调蓄方案和拦蓄入渗方案对河槽暗蓄雨洪资源化的影响。结果 通过不同调蓄方案的对比,采用可调控悬挂截渗坝代替现有截渗坝时,雨洪资源利用率可提高至20.3%;通过不同拦蓄入渗方案的对比,“不清河床+坑塘+拦水堰”方案的雨洪资源入渗量为天然条件下雨洪资源入渗量100倍以上。结论 河槽暗蓄雨洪资源化工程最佳的拦蓄入渗和调蓄组合方案为在“不清河床+坑塘+拦水堰”的情况下采用可调控悬挂截渗坝,可显著提高雨洪资源利用率。

基于Innovus混合放置的布局规划方法优化

随着集成电路后端设计中宏单元数量增多,传统布局规划方法效率低且耗时,而自动布局规划的混合放置(MP)技术存在物理规则违例数量多、电压降大和功耗高等问题。针对传统方式和MP方式的不足,提出了一种优化的MP布局规划方法,通过控制宏单元通道空间和标准单元密度大小、固定边界宏单元位置及脚本修复TSMC芯片集成检查(TCIC)违例的方法解决MP技术存在的问题。研究结果表明,优化的MP方式保留了MP技术的性能、功耗和面积(PPA)优势,且相比于传统方式布线长度优化了28%,时序违例优化了65%,功耗优化了609%。该方案可为多宏单元大规模设计的布局规划提供参考。

6G新型时延多普勒通信范式:OTFS的技术优势、设计挑战、应用与前景

在未来的通信网络中,被广泛期待的第6代移动通信系统(The Sixth Generation of Mobile Communications System,6G)技术将面临诸多挑战,其中包括在高速移动场景下的超高可靠通信问题。正交时频空间(Orthogonal Time Frequency Space,OTFS)调制技术克服了传统通信系统在高速移动环境下多径和多普勒效应的影响,为实现6G超高可靠通信提供了新的可能性。该文首先介绍了OTFS的基本原理、数学模型、干扰与优势分析。然后,归纳分析了OTFS技术在同步、信道估计、信号检测技术上的研究现状。接着,从车联网、无人机、卫星通信、海洋通信4个典型应用场景分析了OTFS的应用趋势。最后,从降低多维匹配滤波器、相位解调和信道估计、硬件实现的复杂度和提高对时频资源的高度利用4个角度探讨了未来研究OTFS需要克服的困难和挑战。

基于模型驱动深度学习的OTFS信道估计

针对单输入单输出(SISO)的正交时频空间(OTFS)调制系统,该文利用一种模型驱动深度学习算法进行OTFS信道估计。该方案首先将去噪近似消息传递(DAMP)算法进行深度展开,利用去噪卷积神经网络代替传统的去噪器,对含噪的时延多普勒信道进行去噪估计,然后提供了状态演化方程来预测可学习去噪近似消息传递(LDAMP)算法的理论归一化均方误差性能。仿真结果表明,相比于其他估计方案,该方案不仅在低信噪比条件下具有优越的性能表现,而且还具有非常好的鲁棒性,在信道路径总数不变时,增加OTFS 2维网格点数量,可以有效提升信道估计精确度。

改进残差网络的肾细胞癌ISUP分级研究

术前预测透明细胞肾细胞癌(clear cell renal cell carcinoma,ccRCC)的分级可有效评估患者的预后并指导临床治疗,但实现精准预测是目前本领域内的一项重要问题。该研究首先确定最优建模的CT类型与网络层数,提出了一种基于改进残差网络的ccRCC的CT影像分级模型,具体包括:利用大卷积操作对图像进行原始特征提取,利用混合注意力模块通过计算特征图中当前空间和临近空间以及当前空间和远距离空间之间的信息交互获取更多有用的特征,使得原始图像特征图在通道维度与空间维度上进行自适应特征细化,利用四个深度卷积网络层提取图像深度特征,并利用改进通道注意力模块产生通道注意力特征图信息,提取更多通道上的交互信息。实验结果表明,增强CT实质期图像和34层残差网络最有利于分级预测模型的开发,所提出的模型的总体加权准确率、AUC、精度、召回率和F1分数分别为90.8%、0.897、90.5%、90.8%、90.9%,各项指标优于其他常见网络结构,因此,该模型在预测ccRCC的国际泌尿病理学学会(International Society of Urological Pathology,ISUP)分级方面有良好的效能,对患者的临床辅助诊断和预后治疗具有重要的理论指导意义。

DWDM中基于预啁啾抑制FWM的优化策略

为了满足波分复用系统中的超高速和长距离传输,需将影响频谱效率和系统性能的四波混频等非线性效应损害降至最低。针对四波混频产生机理,提出了一种抑制波分复用光网络中四波混频效应的方法。该方法分别在有无预啁啾的情况下确定了第一、第二和第三优化优先级参数(如有效面积、信道间距、入纤功率)的单个和组合效应对四波混频效应的影响,对系统误码率进行数值计算,分析系统性能。在16信道系统中,随着有效面积的增加、输入功率的减小和信道间距的增加,光纤中的四波混频效应得以降低,且在预啁啾情况下四波混频效应降至更低。在预啁啾为800 ps/nm时,三种参数优化组合使信道中的最小误码率为8.16×10^(-23),相比无参数优化和预啁啾的光纤通信系统,性能提升132.8 dB。最后,这项工作表明,所提出的基于预啁啾的参数优化策略是密集波分复用系统性能优化的理想方案。