results: 该方法通过利用扩展平衡，在干扰下表现出了与传统OTFS-SCMA系统相比的BER性能改善。Abstract
This letter studies the mechanism of uplink multiple access and jamming suppression in an OTFS system. Specifically, we propose a novel resource hopping mechanism for orthogonal time frequency space (OTFS) systems with delay or Doppler partitioned sparse code multiple access (SCMA) to mitigate the effect of jamming in controlled multiuser uplink. We analyze the non-uniform impact of classic jamming signals such as narrowband interference (NBI) and periodic impulse noise (PIN) in delay-Doppler (DD) domain on OTFS systems. Leveraging turbo equalization, our proposed hopping method demonstrates consistent BER performance improvement under jamming over conventional OTFS-SCMA systems compared to static resource allocation schemes.
摘要
Signal Processing and Learning for Next Generation Multiple Access in 6G
results: 研究表明，学习基本技术可以解决许多传输和处理信号的复杂问题，但是还需要更多的研究来掌握这些技术的潜在。Abstract
Wireless communication systems to date primarily rely on the orthogonality of resources to facilitate the design and implementation, from user access to data transmission. Emerging applications and scenarios in the sixth generation (6G) wireless systems will require massive connectivity and transmission of a deluge of data, which calls for more flexibility in the design concept that goes beyond orthogonality. Furthermore, recent advances in signal processing and learning have attracted considerable attention, as they provide promising approaches to various complex and previously intractable problems of signal processing in many fields. This article provides an overview of research efforts to date in the field of signal processing and learning for next-generation multiple access, with an emphasis on massive random access and non-orthogonal multiple access. The promising interplay with new technologies and the challenges in learning-based NGMA are discussed.
摘要
无线通信系统至今主要依靠资源的正交性来实现用户访问和数据传输。 sixth generation（6G）无线系统中出现的新应用和场景将需要巨量的连接和大量数据传输，这需要更多的灵活性在设计理念中，超出正交性的限制。此外，近年来的信号处理和学习技术的进步吸引了广泛的关注，因为它们在各个领域提供了可能的解决方案。本文提供了到date的研究努力在信号处理和学习领域中，强调巨量随机访问和非正交多访问。新技术的潜在优势和学习基于NGMA的挑战也被讨论。
Achievable Rate Region and Path-Based Beamforming for Multi-User Single-Carrier Delay Alignment Modulation
paper_authors: Xingwei Wang, Haiquan Lu, Yong Zeng, Xiaoli Xu, Jie Xu for:* 这篇论文是为了研究多用户mmWave巨量MIMO通信系统中的延时对Alignment模ulation（DAM）技术。methods:* 这篇论文使用了延时预补做法和路径基于的扫描方法来有效地对多个射频组件进行对齐，从而消除干扰而保留多Path强度提升。results:* 这篇论文表明，在Mt sufficiently large的情况下，通过使用简单的延时预补和每个射频路径基于的MRT扫描方法，单载DAM可以完美地消除干扰和IUI。* 在Mt finite的情况下，该论文研究了多用户DAM系统的可达速率区的可能性。* 该论文提出了三种低复杂度的每个射频路径基于的扫描策略，并研究了这些策略对系统的可达速率的影响。* 最后，该论文提供了对两个参考方案（基于最强射频路径基于的扫描和OFDM）的比较，并证明DAM在高 spatial resolution和多Path多杂性下 achieve higher spectral efficiency和/或 lower peak-to-average-ratio。Abstract
Delay alignment modulation (DAM) is a novel wideband transmission technique for mmWave massive MIMO systems, which exploits the high spatial resolution and multi-path sparsity to mitigate ISI, without relying on channel equalization or multi-carrier transmission. In particular, DAM leverages the delay pre-compensation and path-based beamforming to effectively align the multi-path components, thus achieving the constructive multi-path combination for eliminating the ISI while preserving the multi-path power gain. Different from the existing works only considering single-user DAM, this paper investigates the DAM technique for multi-user mmWave massive MIMO communication. First, we consider the asymptotic regime when the number of antennas Mt at BS is sufficiently large. It is shown that by employing the simple delay pre-compensation and per-path-based MRT beamforming, the single-carrier DAM is able to perfectly eliminate both ISI and IUI. Next, we consider the general scenario with Mt being finite. In this scenario, we characterize the achievable rate region of the multi-user DAM system by finding its Pareto boundary. Specifically, we formulate a rate-profile-constrained sum rate maximization problem by optimizing the per-path-based beamforming. Furthermore, we present three low-complexity per-path-based beamforming strategies based on the MRT, zero-forcing, and regularized zero-forcing principles, respectively, based on which the achievable sum rates are studied. Finally, we provide simulation results to demonstrate the performance of our proposed strategies as compared to two benchmark schemes based on the strongest-path-based beamforming and the prevalent OFDM, respectively. It is shown that DAM achieves higher spectral efficiency and/or lower peak-to-average-ratio, for systems with high spatial resolution and multi-path diversity.
摘要
延迟匹配模ulation（DAM）是一种新的宽带传输技术，用于mmWave巨量MIMO系统，可以利用高度空间分解和多path稀烈性来缓解混合干扰（ISI），不需要通道平衡或多帧传输。具体来说，DAM利用延迟预补和路径基本形式 beamforming来有效地对多path组分进行匹配，从而实现了构建多path组分的积加，以消除ISI而保留多path功率增加。与现有作品只考虑单用户DAM不同，本文研究了DAM技术在多用户mmWave巨量MIMO通信中的应用。首先，我们考虑了Mt的很大值时的极限情况。 results show that by employing simple delay pre-compensation and per-path-based MRT beamforming, the single-carrier DAM can perfectly eliminate both ISI and IUI.然后，我们考虑了Mt finite值的普通情况。在这种情况下，我们定义了DAM系统的可达性区的边界，并通过优化每个路径基本形式 beamforming来实现最大化总bitrate。 Specifically, we formulate a rate-profile-constrained sum rate maximization problem by optimizing the per-path-based beamforming.此外，我们还提出了三种低复杂度的每个路径基本形式 beamforming策略，基于MRT、零干扰和正则化零干扰原理。这些策略的实现可以帮助提高系统的可达性和 Spectral efficiency。最后，我们通过对两种参考方案（基于最强路径基本形式 beamforming和普遍OFDM）进行比较，提供了实验结果，以证明DAM在高度空间分解和多path稀烈性的系统中可以 дости得更高的 spectral efficiency和/或更低的 peak-to-average-ratio。
Bayesian estimation and reconstruction of marine surface contaminant dispersion
paper_authors: Yang Liu, Christopher M. Harvey, Frederick E. Hamlyn, Cunjia Liu for: 这个研究旨在提供一个精度估计和重建海洋环境中潜在危害物质泄漏的框架，以便与环境监测敏感器网络或移动敏感器相结合。methods: 这个研究使用了基本的扩散-渗透偏微方程（PDE）来表示物质泄漏的总体分布，并使用动态适应finite-element方法（FEM）将其在非均匀流场中的空间灵活分解。在扩散过程中，研究者们考虑了感知器的不准确现象，包括漏掉检测和信号量化。results: 研究结果表明，提出的框架在实际的油污泄漏事件中的波罗的海 demonstrate its efficacy in reconstructing spatio-temporal dispersion in the presence of imperfect measurements.Abstract
Discharge of hazardous substances into the marine environment poses a substantial risk to both public health and the ecosystem. In such incidents, it is imperative to accurately estimate the release strength of the source and reconstruct the spatio-temporal dispersion of the substances based on the collected measurements. In this study, we propose an integrated estimation framework to tackle this challenge, which can be used in conjunction with a sensor network or a mobile sensor for environment monitoring. We employ the fundamental convection-diffusion partial differential equation (PDE) to represent the general dispersion of a physical quantity in a non-uniform flow field. The PDE model is spatially discretised into a linear state-space model using the dynamic transient finite-element method (FEM) so that the characterisation of time-varying dispersion can be cast into the problem of inferring the model states from sensor measurements. We also consider imperfect sensing phenomena, including miss-detection and signal quantisation, which are frequently encountered when using a sensor network. This complicated sensor process introduces nonlinearity into the Bayesian estimation process. A Rao-Blackwellised particle filter (RBPF) is designed to provide an effective solution by exploiting the linear structure of the state-space model, whereas the nonlinearity of the measurement model can be handled by Monte Carlo approximation with particles. The proposed framework is validated using a simulated oil spill incident in the Baltic sea with real ocean flow data. The results show the efficacy of the developed spatio-temporal dispersion model and estimation schemes in the presence of imperfect measurements. Moreover, the parameter selection process is discussed, along with some comparison studies to illustrate the advantages of the proposed algorithm over existing methods.
摘要
排放危险物质到海洋环境中存在严重的风险，对公众健康和生态系统都具有潜在的威胁。在这种情况下，需要精准地估计排放源的强度和杂散的空间时间特征。本研究提出一种集成估计框架，可以与监测敏感器网络或移动监测器相结合使用。我们采用基本的扩散混合方程（PDE）来表示物质扩散的总体特征，并将PDE方程在空间上精度化为线性状态空间模型（FEM），以便在排放源的特征上进行时间变化的描述。我们还考虑了感知现象的不准确性，包括感知错误和信号量化，这些现象在使用敏感器网络时经常出现。这种复杂的感知过程引入了非线性到 bayesian 估计过程中。我们采用Rao-Blackwellised particle filter（RBPF）来提供有效的解决方案，通过利用状态空间模型的线性结构，同时处理测量模型中的非线性。我们在 simulated oil spill incident 中使用 Baltic sea 的实际海流数据进行验证，结果显示我们提出的空间时间杂散模型和估计方法在受到不准确测量的情况下具有效果。此外，我们还讨论了参数选择过程，并进行了与其他方法进行比较，以 Illustrate 我们的方法的优势。
Message Passing Based Block Sparse Signal Recovery for DOA Estimation Using Large Arrays
results: 模拟结果表明提议方法的性能较高。Abstract
This work deals with directional of arrival (DOA) estimation with a large antenna array. We first develop a novel signal model with a sparse system transfer matrix using an inverse discrete Fourier transform (DFT) operation, which leads to the formulation of a structured block sparse signal recovery problem with a sparse sensing matrix. This enables the development of a low complexity message passing based Bayesian algorithm with a factor graph representation. Simulation results demonstrate the superior performance of the proposed method.
摘要
这个工作关于方向来源估计（DOA）测量使用大天线数组。我们首先开发了一种新的信号模型，使用反对排阵 Fourier 转换（DFT）操作获得简单系统传输矩阵，从而导致了一个嵌入式块简单信号恢复问题，其中感知矩阵具有稀疏性。这使得我们可以开发一种低复杂度的消息传递基于 bayesian 算法，并使用因素图表示。实验结果表明我们的方法表现更好。Note: The translation is in Simplified Chinese, which is the standard writing system used in mainland China. If you need Traditional Chinese, please let me know.
A Spatial Sigma-Delta Approach to Mitigation of Power Amplifier Distortions in Massive MIMO Downlink
results: 通过数字预修正（DPD）和符号级precoding（SLP） schemes，可以提高系统性能。Abstract
In massive multiple-input multiple-output (MIMO) downlink systems, the physical implementation of the base stations (BSs) requires the use of cheap and power-efficient power amplifiers (PAs) to avoid high hardware cost and high power consumption. However, such PAs usually have limited linear amplification ranges. Nonlinear distortions arising from operation beyond the linear amplification ranges can significantly degrade system performance. Existing approaches to handle the nonlinear distortions, such as digital predistortion (DPD), typically require accurate knowledge, or acquisition, of the PA transfer function. In this paper, we present a new concept for mitigation of the PA distortions. Assuming a uniform linear array (ULA) at the BS, the idea is to apply a Sigma-Delta ($\Sigma \Delta$) modulator to spatially shape the PA distortions to the high-angle region. By having the system operating in the low-angle region, the received signals are less affected by the PA distortions. To demonstrate the potential of this spatial $\Sigma \Delta$ approach, we study the application of our approach to the multi-user MIMO-orthogonal frequency division modulation (OFDM) downlink scenario. A symbol-level precoding (SLP) scheme and a zero-forcing (ZF) precoding scheme, with the new design requirement by the spatial $\Sigma \Delta$ approach being taken into account, are developed. Numerical simulations are performed to show the effectiveness of the developed $\Sigma \Delta$ precoding schemes.
摘要
在大规模多输入多出力（MIMO）下行系统中，基站（BS）的物理实现需要使用便宜且功率低的功率增强器（PA），以避免高硬件成本和高功率消耗。然而，这些PA通常有有限的线性增强范围。操作 beyond这些范围的非线性扭曲可以很大程度地降低系统性能。现有的抗扭曲方法，如数字预修正（DPD），通常需要准确地知道或获得PA传输函数。在本文中，我们提出了一种新的抗扭曲方法。假设基站使用uniform linear array（ULA），我们的想法是通过空间Sigma-Delta（$\Sigma \Delta$)模ulator来形态地扭曲PA扭曲到高角度区域。由于系统在低角度区域运行，接收信号受到PA扭曲的影响较少。为了证明这种空间$\Sigma \Delta$方法的潜在效果，我们对多用户MIMO-orthogonal frequency division modulation（OFDM）下行enario进行了研究。我们开发了一种符号级 precoding（SLP）和零强制（ZF） precoding schemes，并考虑了新的设计要求。我们对 numerically simulations 进行了测试，以证明我们的 $\Sigma \Delta$ precoding schemes 的有效性。
Evaluation of onboard sensors for track geometry monitoring against conventional track recording measurements
methods: 研究人员设计了一种在列车上的数据获取系统（DAQ）的原型，并在布里斯班郊区铁路网络上进行了测量。 comparison of accelerometer-based results vs TRC recordings 表明，在车厢上安装的加速仪最佳妥协是距离源最近，但免疫干扰噪声的选择。
results: 研究发现，在左右两侧的 bogie 上安装的两个垂直加速仪可以提供好的量化估计垂直对齐，而两个水平加速仪的测量结果与 TRC 记录相关。这些发现表明，使用两个 bogie 上的 MEMS 加速仪，可以提供量化的垂直对齐和水平对齐的估计，并且可以描述轨道网络中水平对齐的趋势。Abstract
The main objective of this paper is to assess the feasibility and accuracy of inferring key track condition parameters, e.g., vertical alignment and horizontal alignment of the rails, using onboard micro-electro-mechanical-system (MEMS) accelerometers. To achieve this aim, a prototype of an onboard data acquisition system (DAQ) was designed and installed on a track recording car (TRC) and a measurement campaign was conducted on an extensive portion of the Brisbane Suburban railway network. Comparison of the accelerometer-based results vs TRC recordings have shown that accelerometers installed on the bogie are the best compromise between proximity to the source and insensitivity to impulsive noise. Moreover, it was found that two vertical bogie accelerometers (left and right side) provide a good quantitative estimate of vertical alignment and that strong correlations with TRC measurements exist for lateral MEMS accelerometer measurements (horizontal alignment). These findings suggest that two bogie MEMS accelerometers with two measurement axes (vertical and lateral) are an effective system and can provide quantitative estimates of vertical alignment and trends in the geographical distribution of horizontal alignment.
摘要
本文的主要目标是评估使用在列车上的微型电子机械系统（MEMS）加速仪测量铁轨的重要参数，如垂直平行和水平平行。为达到这个目标，我们设计了一种在列车上的数据采集系统（DAQ）的原型，并在布里斯班郊区铁路网络上进行了评估。对比加速仪测量结果和TRC记录结果表明，在车厢上安装的加速仪最佳的折衔是与源之间的距离和干扰噪音的敏感度之间的平衡。此外，我们发现了两个垂直车厢加速仪（左右两侧）可以提供好的量化估计垂直平行，并且发现了两个车厢MEMS加速仪的两个测量轴（垂直和水平）可以提供有关垂直平行的趋势和地理分布的水平平行的量化估计。这些发现表明，两个车厢MEMS加速仪是一个有效的系统，可以提供有关垂直平行和水平平行的量化估计。
Concept for an Automatic Annotation of Automotive Radar Data Using AI-segmented Aerial Camera Images
results: 在测量中，使用这种方法自动标注了589名行人在雷达数据中，并且只用2分钟的时间Here’s the translation of the abstract in English:
for: Automatically annotate automotive radar data with AI-segmented aerial camera images
methods: Use UAV camera images to find and map instances and segments in the ground plane onto radar images, and apply the detected instances and segments as labels for the radar data
results: Demonstrated effectiveness and scalability in measurements, where 589 pedestrians in the radar data were automatically labeled within 2 minutes.Abstract
This paper presents an approach to automatically annotate automotive radar data with AI-segmented aerial camera images. For this, the images of an unmanned aerial vehicle (UAV) above a radar vehicle are panoptically segmented and mapped in the ground plane onto the radar images. The detected instances and segments in the camera image can then be applied directly as labels for the radar data. Owing to the advantageous bird's eye position, the UAV camera does not suffer from optical occlusion and is capable of creating annotations within the complete field of view of the radar. The effectiveness and scalability are demonstrated in measurements, where 589 pedestrians in the radar data were automatically labeled within 2 minutes.
摘要
Ground Truth Generation Algorithm for Medium-Frequency R-Mode Skywave Detection
results: 研究人员发现MF R-Mode在白天和黑夜之间表现出显著的性能差异，这是由GNSS信号在离子层反射后引起的天体干扰所致。在这项研究中，我们提出了一种可以生成天体干扰的背景真实场景生成算法，并在实验数据上进行了 validate。Abstract
With the advancement of transportation vehicles, the importance and utility of navigation systems providing positioning, navigation, and timing (PNT) information have been increasing. Global navigation satellite systems (GNSS) are widely used navigation systems, but they are vulnerable to radio frequency interference (RFI), resulting in disruptions of satellite navigation signals. Recognizing this limitation, extensive research is being conducted on alternative navigation systems. In the maritime industry, ongoing research focuses on a groundbased integrated navigation system called R-Mode. R-Mode utilizes medium frequency (MF) differential GNSS (DGNSS) and very high-frequency data exchange system (VDES) signals as ranging signals for positioning and incorporates the existing ground-based navigation system known as enhanced long-range navigation (eLoran). However, MF R-Mode, which uses MF DGNSS signals for positioning, exhibits significant performance differences between daytime and nighttime due to skywave interference caused by signals reflecting off the ionosphere. In this study, we propose a skywave ground truth generation algorithm that is crucial for studying mitigation methods for MF R-Mode skywave interference. Furthermore, we demonstrate the proposed algorithm using field-test data.
摘要
Translation in Simplified Chinese:随着交通运输车辆的发展，提供位置、导航和时间信息的导航系统的重要性和实用性日益增加。全球卫星导航系统（GNSS）是广泛使用的导航系统，但它们受到广播频率干扰（RFI）的影响，导致卫星导航信号的中断。认识到这些限制，广泛的研究在进行 altenative 导航系统。在海事业中，进行的研究主要关注一种基于地面的集成导航系统，即R-Mode。R-Mode 使用中频 differential GNSS（DGNSS）和射频数据交换系统（VDES）信号作为距离测量信号，并 integra 现有的地面导航系统，即增强距离导航（eLoran）。然而，MF R-Mode，使用MF DGNSS信号进行位置测量，在日间和夜间 exhibits 显著的性能差异，这是由于天顶层干扰，即信号反射在离子层。在这项研究中，我们提出了天顶层真实数据生成算法，这是关键的 для研究MF R-Mode 天顶层干扰的mitigation方法。此外，我们使用实验数据来证明提出的算法。
Empirical Modeling of Variance in Medium Frequency R-Mode Time-of-Arrival Measurements
results: 通过应用loran方法来计算时间接收标准差，并估算TOA测量方差参数Here’s the same information in English:
for: Improving the accuracy of performance simulation for the medium frequency R-Mode system
methods: Modeling the variance of time-of-arrival measurements based on actual data, inspired by the method used to calculate the standard deviation of time-of-reception measurements in Loran
results: Estimating the parameters for modeling the variance of TOA measurements using the Loran method and applying it to the MF R-Mode system.Abstract
The R-Mode system, an advanced terrestrial integrated navigation system, is designed to address the vulnerabilities of global navigation satellite systems (GNSS) and explore the potential of a complementary navigation system. This study aims to enhance the accuracy of performance simulation for the medium frequency (MF) R-Mode system by modeling the variance of time-of-arrival (TOA) measurements based on actual data. Drawing inspiration from the method used to calculate the standard deviation of time-of-reception (TOR) measurements in Loran, we adapted and applied this approach to the MF R-Mode system. Data were collected from transmitters in Palmi and Chungju, South Korea, and the parameters for modeling the variance of TOA were estimated.
摘要
R-Mode系统，一个进阶的陆地综合导航系统，旨在解决全球导航卫星系统（GNSS）的漏洞和探索一个辅助导航系统的潜力。本研究旨在提高中频R-Mode系统的性能模拟精度，基于实际数据模型时间到来（TOA）测量的变化。将 Loran中用于计算时间接收变化的方法作为灵感，我们适应并应用这种方法到中频R-Mode系统中。数据来自韩国Palmi和Chungju的传送器，并估算了模型时间到来的变化。