for: 这 paper 研究了无机体 massive multiple-input multiple-output (CF-mMIMO) 系统，它们包括同时无线信息和能量传输 (SWIPT) for 分开的信息用户 (IUs) 和能量用户 (EUs) in Internet of Things (IoT) 网络。
methods: 作者提出了一种联合Access Point (AP) 操作模式选择和功率控制设计，其中一些 APs 专门用于向 EUs 传输能量，而其他 APs 专门用于向 IUs 传输信息。
results: 作者的数字结果表明，提出的 AP 操作模式选择算法可以提供高达 76% 和 130% 的性能提升 compared to random AP 操作模式选择，具体来说是 maximizing the total harvested energy (HE) for EUs, while satisfying constraints on spectral efficiency (SE) for individual IUs and minimum HE for individual EUs.Abstract
This paper studies cell-free massive multiple-input multiple-output (CF-mMIMO) systems incorporating simultaneous wireless information and power transfer (SWIPT) for separate information users (IUs) and energy users (EUs) in Internet of Things (IoT) networks. To optimize both the spectral efficiency (SE) of IUs and harvested energy (HE) of EUs, we propose a joint access point (AP) operation mode selection and power control design, wherein certain APs are designated for energy transmission to EUs, while others are dedicated to information transmission to IUs. We investigate the problem of maximizing the total HE for EUs, considering constraints on SE for individual IUs and minimum HE for individual EUs. Our numerical results showcase that the proposed AP operation mode selection algorithm can provide up to $76\%$ and $130\%$ performance gains over random AP operation mode selection with and without power control, respectively.
摘要
We investigate the problem of maximizing the total HE for EUs, while ensuring constraints on SE for individual IUs and minimum HE for individual EUs. Our numerical results show that the proposed AP operation mode selection algorithm can provide up to 76% and 130% performance gains over random AP operation mode selection with and without power control, respectively.
A Framework for Developing and Evaluating Algorithms for Estimating Multipath Propagation Parameters from Channel Sounder Measurements
results: 结果表明，使用 CLEAN 算法可以获得比较可靠的估计，SAGE 和 RiMAX 算法可以进一步改进估计结果，但是 RiMAX 还可以捕捉到干扰的散射效应。Abstract
A framework is proposed for developing and evaluating algorithms for extracting multipath propagation components (MPCs) from measurements collected by channel sounders at millimeter-wave frequencies. Sounders equipped with an omnidirectional transmitter and a receiver with a uniform planar array (UPA) are considered. An accurate mathematical model is developed for the spatial frequency response of the sounder that incorporates the non-ideal cross-polar beampatterns for the UPA elements. Due to the limited Field-of-View (FoV) of each element, the model is extended to accommodate multi-FoV measurements in distinct azimuth directions. A beamspace representation of the spatial frequency response is leveraged to develop three progressively complex algorithms aimed at solving the singlesnapshot maximum likelihood estimation problem: greedy matching pursuit (CLEAN), space-alternative generalized expectationmaximization (SAGE), and RiMAX. The first two are based on purely specular MPCs whereas RiMAX also accommodates diffuse MPCs. Two approaches for performance evaluation are proposed, one with knowledge of ground truth parameters, and one based on reconstruction mean-squared error. The three algorithms are compared through a demanding channel model with hundreds of MPCs and through real measurements. The results demonstrate that CLEAN gives quite reasonable estimates which are improved by SAGE and RiMAX. Lessons learned and directions for future research are discussed.
摘要
一种框架被提议用于开发和评估抽取多路干扰组件（MPC）的算法，该算法使用频率上的通道测量仪器进行 millimeter-wave 频率收集数据。这些测量仪器包括一个全irectional 发射器和一个具有均匀平面阵列（UPA）的接收器。为了更好地模型测量仪器的空间频率响应，一个精确的数学模型被开发，该模型考虑了 UPA 元素的非理想交叉束波响应。由于每个元素的视场有限，模型进一步扩展以处理多个视场的测量。通过使用 beamspace 表示法，开发了三种不同的算法，以解决单个快照最大可能性估计问题：排序匹配缓解（CLEAN）、空间替换总体预期最大化（SAGE）和 RiMAX。前两个算法基于纯specular MPC，而 RiMAX 还处理 diffuse MPC。两种方法被提议用于性能评估：一种基于地面参数的知情预测，另一种基于重建平均方差。这三种算法在一种复杂的通道模型和实际测量中进行比较，结果表明，CLEAN 提供了相对较好的估计，SAGE 和 RiMAX 则提供了更好的估计。文章结尾还讨论了学习的教训和未来研究的方向。
Free space optics communication system design using iterative optimization
results: 比对文献，实现10Gbps的数据传输速率，在不同天气条件下，visibility距离、质量因子、BER和眼图都有较好的表现Abstract
Free Space Optics (FSO) communication provides attractive bandwidth enhancement with unlicensed bands worldwide spectrum. However, the link capacity and availability are the major concern in the different atmospheric conditions. The reliability of the link is highly dependent on weather conditions that attenuate the signal strength. Hence, this study focuses to mitigate the weather and geographic effects using iterative optimization on FSO communication. The optimization maximizes the visibility distance while guaranteeing the reliability by minimizing the Bit Error Rate (BER). The wireless optical communication system is designed for the data rate of 10 Gbps. The performance of the proposed wireless optical communication is compared against the literature in terms of visibility distance, quality factor, BER, and Eye diagram at different atmospheric conditions. The simulation results have shown that the proposed work has achieved better performance.
摘要
自由空间光学（FSO）通信提供了广阔的带宽提升，但链接容量和可用性在不同的天气条件下是主要的问题。链接可靠性高度依赖于天气条件的吸收强度，因此这个研究旨在通过迭代优化 mitigate 天气和地理效应，以提高FSO通信的可靠性。优化寻味距离，并保证可靠性，最小化Bit Error Rate（BER）。这个无线光学通信系统设计了10Gbps的数据速率。与文献比较，这个提案的性能在不同的天气条件下表现较好，visibility distance、质量因子、BER和eye diagram都有所提高。
How secure is the time-modulated array-enabled ofdm directional modulation?
for: 研究了时间模ulated arrays（TMA）发送的 ortogonal frequency division multiplexing（OFDM）波形的物理层安全性，并表明了攻击者可以破坏scrambling。
methods: 使用独立组分分析（ICA）技术来分离数据符号和TMA参数，并利用扩展和Permutation ambiguity resolved by exploiting the Toeplitz structure of the mixing matrix and knowledge of data constellation, OFDM specifics, and TMA parameter selection rules。
results: 表明了在ICA技术的帮助下，攻击者可以从混乱的信号中提取数据符号和TMA参数，并且引入了一种新的TMA实现方式来防止攻击。Abstract
Time-modulated arrays (TMA) transmitting orthogonal frequency division multiplexing (OFDM) waveforms achieve physical layer security by allowing the signal to reach the legitimate destination undistorted, while making the signal appear scrambled in all other directions. In this paper, we examine how secure the TMA OFDM system is, and show that it is possible for the eavesdropper to defy the scrambling. In particular, we show that, based on the scrambled signal, the eavesdropper can formulate a blind source separation problem and recover data symbols and TMA parameters via independent component analysis (ICA) techniques. We show how the scaling and permutation ambiguities arising in ICA can be resolved by exploiting the Toeplitz structure of the corresponding mixing matrix, and knowledge of data constellation, OFDM specifics, and the rules for choosing TMA parameters. We also introduce a novel TMA implementation to defend the scrambling against the eavesdropper.
摘要
时间模拟数组（TMA）发送 orthogonal frequency division multiplexing（OFDM）波形可以实现物理层安全性，使信号只能正确地达到合法目标，而在其他方向都显示混乱。在这篇论文中，我们研究了TMA OFDM系统的安全性，并显示了可以由侦测者违规破坏混乱。特别是，我们表明，基于混乱的信号，侦测者可以将问题转化为盲源分离问题，并通过独立元分析（ICA）技术来恢复数据符号和TMA参数。我们解决了涉及到ICA的缩放和排序歧义，通过利用混合矩阵的托勒茨结构和数据集、OFDM特点、TMA参数选择规则。此外，我们还介绍了一种新的TMA实现方式，以防止混乱被侦测者破坏。
Map2Schedule: An End-to-End Link Scheduling Method for Urban V2V Communications
paper_authors: Lihao Zhang, Haijian Sun, Jin Sun, Ramviyas Parasuraman, Yinghui Ye, Rose Qingyang Hu
For: 本研究的目的是设计一个可以在城市环境中实现高性能的车辆间通讯链路选择方法。* Methods: 本研究使用了机器学习技术，包括卷积神经网络和 гра embedding 模型，从城市地图和车辆位置中估计频率state information，并对最佳链路选择策略进行优化。* Results: 本研究的结果显示，提案的方法可以在城市环境中实现高精度的频率state estimation，并且具有较低的过程复杂度和延迟。Abstract
Urban vehicle-to-vehicle (V2V) link scheduling with shared spectrum is a challenging problem. Its main goal is to find the scheduling policy that can maximize system performance (usually the sum capacity of each link or their energy efficiency). Given that each link can experience interference from all other active links, the scheduling becomes a combinatorial integer programming problem and generally does not scale well with the number of V2V pairs. Moreover, link scheduling requires accurate channel state information (CSI), which is very difficult to estimate with good accuracy under high vehicle mobility. In this paper, we propose an end-to-end urban V2V link scheduling method called Map2Schedule, which can directly generate V2V scheduling policy from the city map and vehicle locations. Map2Schedule delivers comparable performance to the physical-model-based methods in urban settings while maintaining low computation complexity. This enhanced performance is achieved by machine learning (ML) technologies. Specifically, we first deploy the convolutional neural network (CNN) model to estimate the CSI from street layout and vehicle locations and then apply the graph embedding model for optimal scheduling policy. The results show that the proposed method can achieve high accuracy with much lower overhead and latency.
摘要
城市往返自动车（V2V）链接调度问题是一个具有挑战性的问题。其主要目标是找到调度策略，以最大化系统性能（通常是每个链接的总容量或能效性）。由于每个链接可以受到所有活跃链接的干扰，调度问题变成了一个 combinatorial 整数编程问题，通常不会随着 V2V 对的数量很好地扩展。此外，链接调度需要准确的通道状态信息（CSI），这是在高速移动的情况下很难以估计准确。在这篇论文中，我们提出了一种名为 Map2Schedule 的综合urban V2V 链接调度方法，可以直接从城市地图和车辆位置生成 V2V 调度策略。Map2Schedule 可以在城市环境下达到与物理模型基于方法相当的性能，同时保持低的计算复杂度。这种提高的性能是基于机器学习（ML）技术。具体来说，我们首先部署了卷积神经网络（CNN）模型，以估计从街道布局和车辆位置中的 CSI，然后应用图像嵌入模型进行优化调度策略。结果显示，我们的方法可以达到高精度，并且带有远低的开销和延迟。
Fusion framework and multimodality for the Laplacian approximation of Bayesian neural networks
results: 在使用两个经典的图像分类任务（MNIST和CFAR10）和摄像头拍摄的瑞典森林中的狮子摄像头拍摄图像序列进行示例，这种融合策略和提出的扩展都能够提高误差calibration的性能。Abstract
This paper considers the problem of sequential fusion of predictions from neural networks (NN) and fusion of predictions from multiple NN. This fusion strategy increases the robustness, i.e., reduces the impact of one incorrect classification and detection of outliers the \nn has not seen during training. This paper uses Laplacian approximation of Bayesian NNs (BNNs) to quantify the uncertainty necessary for fusion. Here, an extension is proposed such that the prediction of the NN can be represented by multimodal distributions. Regarding calibration of the estimated uncertainty in the prediction, the performance is significantly improved by having the flexibility to represent a multimodal distribution. Two class classical image classification tasks, i.e., MNIST and CFAR10, and image sequences from camera traps of carnivores in Swedish forests have been used to demonstrate the fusion strategies and proposed extension to the Laplacian approximation.
摘要
这篇论文考虑了神经网络（NN）的顺序融合和多个NN的融合策略，这种融合策略可以提高鲁棒性，即减少一个错误分类的影响和探测器在训练过程中没有看到的异常值。这篇论文使用朗尼均方（Laplacian approximation）来评估神经网络（BNN）的不确定性。在这种情况下，一种扩展是提出的，即预测神经网络可以表示多模态分布。对于预测 uncertainty 的准确性的调整，表现得非常改善，这是因为可以表示多模态分布的灵活性。在两个分类任务中，即MNIST和CFAR10，以及从瑞典雨林中的摄像头拍摄的车辆猎食行为图像序列中，使用了这种融合策略和提出的扩展来示示。
Low Complexity Algorithms for Mission Completion Time Minimization in UAV-Based ISAC Systems
results: 研究发现，通过实际仿真参数，第一种算法可以保持至少20%的时间提升，而第二种算法可以将总完成时间减少至少7倍。Abstract
The inherent support of sixth-generation (6G) systems enabling integrated sensing and communications (ISAC) paradigm greatly enhances the application area of intelligent transportation systems (ITS). One of the mission-critical applications enabled by these systems is disaster management, where ISAC functionality may not only provide localization but also provide users with supplementary information such as escape routes, time to rescue, etc. In this paper, by considering a large area with several locations of interest, we formulate and solve the optimization problem of delivering task parameters of the ISAC system by optimizing the UAV speed and the order of visits to the locations of interest such that the mission time is minimized. The formulated problem is a mixed integer non-linear program which is quite challenging to solve. To reduce the complexity of the solution algorithms, we propose two circular trajectory designs. The first algorithm finds the optimal UAV velocity and radius of the circular trajectories. The second algorithm finds the optimal connecting points for joining the individual circular trajectories. Our numerical results reveal that, with practical simulation parameters, the first algorithm provides a time saving of at least $20\%$, while the second algorithm cuts down the total completion time by at least $7$ times.
摘要
sixth-generation (6G) 系统内置的集成感知通信（ISAC）模式可以大幅扩展智能交通系统（ITS）的应用范围。 ISAC 功能可以不仅提供地理位置信息，还可以为用户提供补充信息，如避险 Routes、救援时间等。 在这篇论文中，我们通过考虑一个大面积的多个关注点来形式化和解决 ISAC 系统交由任务参数的优化问题，以最小化任务时间。 我们提出了两种圆形轨迹设计来降低解题算法的复杂性。 首先，我们找到了最优的 UAV 速度和圆形轨迹半径。 其次，我们找到了连接各个圆形轨迹的最优连接点。 我们的数据分析表明，使用实际参数进行模拟，首 algorithm 可以保证在至少20%的时间上减少任务时间，而第二 algorithm 可以将总完成时间减少至少7倍。
Maximization of minimum rate in MIMO OFDM RIS-assisted Broadcast Channels
paper_authors: Mohammad Soleymani, Ignacio Santamaria, Aydin Sezgin, Eduard Jorswieck
for: 提高无线通信系统的频率效率
methods: 优化RIS元素，并joint precoding和RIS优化问题
results: RIS可以在多输入多出力OFDM广播频道中提高系统性能，即使每个子带中RIS元素很少。Abstract
Reconfigurable intelligent surface (RIS) is a promising technology to enhance the spectral efficiency of wireless communication systems. By optimizing the RIS elements, the performance of the overall system can be improved. Yet, in contrast to single-carrier systems, in multi-carrier systems, it is not possible to independently optimize RIS elements at each sub-carrier, which may reduce the benefits of RIS in multi-user orthogonal frequency division multiplexing (OFDM) systems. To this end, we investigate the effectiveness of RIS in multiple-input, multiple-output (MIMO) OFDM broadcast channels (BC). We formulate and solve a joint precoding and RIS optimization problem. We show that RIS can significantly improve the system performance even when the number of RIS elements per sub-band is very low.
摘要
可重配置智能表面（RIS）是一种扩展无线通信系统的spectral efficiency的技术。通过优化RIS元素，整体系统的性能可以得到改善。然而，在多个卡通系统中，不能独立地优化RIS元素每个子带，这可能减少RIS在多用户orthogonal frequency division multiplexing（OFDM）系统中的 beneficial effects。为此，我们研究了RIS在多输入多出力（MIMO）OFDM广播频道（BC）中的效果。我们建立了一个共同预编和RIS优化问题，并证明RIS可以在每个子带中具有很少的RIS元素时 Still significantly improve the system performance。
Underwater Sound Speed Profile Construction: A Review
methods: 主流方法包括直接测量SSP和SSP反推。 direct measurement方法比较精度高，但通常需要很长时间。而反推方法可以提高实时性，但精度不及直接测量方法。
results: 当前主流方法仅能在各种水下观测系统覆盖区域内进行SSP构建，无法预测未来时间内声速分布。未来研究将注重多源数据的共同利用，提供不同精度和实时要求的声速分布估计服务，而无需水下观测系统。Abstract
Real--time and accurate construction of regional sound speed profiles (SSP) is important for building underwater positioning, navigation, and timing (PNT) systems as it greatly affect the signal propagation modes such as trajectory. In this paper, we summarizes and analyzes the current research status in the field of underwater SSP construction, and the mainstream methods include direct SSP measurement and SSP inversion. In the direct measurement method, we compare the performance of popular international commercial temperature, conductivity, and depth profilers (CTD). While for the inversion methods, the framework and basic principles of matched field processing (MFP), compressive sensing (CS), and deep learning (DL) for constructing SSP are introduced, and their advantages and disadvantages are compared. The traditional direct measurement method has good accuracy performance, but it usually takes a long time. The proposal of SSP inversion method greatly improves the convenience and real--time performance, but the accuracy is not as good as the direct measurement method. Currently, the SSP inversion relies on sonar observation data, making it difficult to apply to areas that couldn't be covered by underwater observation systems, and these methods are unable to predict the distribution of sound velocity at future times. How to comprehensively utilize multi-source data and provide elastic sound velocity distribution estimation services with different accuracy and real-time requirements for underwater users without sonar observation data is the mainstream trend in future research on SSP construction.
摘要
实时准确地建立地区声速 Profil (SSP) 非常重要，因为它会影响信号传播模式，如轨迹。在这篇论文中，我们总结了现有领域的研究状况，主流方法包括直接测量SSP和SSP反推。直接测量方法中，我们比较了流行的国际商业温度、电导和深度测量仪器（CTD）的性能。而反推方法中，我们介绍了匹配场处理（MFP）、压缩感知（CS）和深度学习（DL）的框架和基本原则，并比较了它们的优劣点。直接测量方法具有良好的精度表现，但通常需要很长时间。反推方法可以大幅提高实时性，但精度不如直接测量方法。当前，SSP反推方法仅仅基于声波观测数据，因此在没有声波观测系统覆盖的区域无法应用，并且无法预测未来时间的声速分布。未来研究应该尝试通过多源数据的共同利用，为无声波观测数据的水下用户提供不同精度和实时需求的声速分布估计服务。
Analysing of 3D MIMO Communication Beamforming in Linear and Planar Arrays
for: investigate the performance of different beamforming techniques for MIMO communication systems with planar arrays.
methods: covariance-based MIMO communication waveform method, MATLAB simulations.
results: 3D beam patterns generated by these constellations.Here’s the full text in Simplified Chinese:
for: 研究不同干扰方法的MIMO通信系统平面阵列性能.
methods: 协方差基于MIMO通信波形方法, MATLAB仿真.
results: 平面阵列Generated的3D扩散模式.Abstract
Massive multiple-input multiple-output (MIMO) systems are expected to play a crucial role in the 5G wireless communication systems. These advanced systems, which are being deployed since 2021, offer significant advantages over conventional communications generations. Unlike previous versions of communication, MIMO systems can transmit various probing signals through their antennas, which may or may not be correlated with each other. This waveform diversity provided by MIMO communication enables enhanced capabilities and improved performance. Numerous research papers have proposed different approaches for beamforming in MIMO communication. We anticipate that our research will provide valuable insights into the performance of different beamforming techniques for MIMO communication systems with planar arrays. We will investigate the 3D beam patterns generated by these constellations using the covariance-based MIMO communication waveform method. MATLAB simulations will be utilized to analyze and evaluate the performance of these methods.
摘要
巨大多输入多输出（MIMO）系统在5G无线通信系统中将扮演关键角色。这些高级系统自2021年起已经被部署，与过去的通信生成器相比，它们提供了重要的优势。与过去的通信不同，MIMO系统可以通过其天线传输多种探测信号，这些信号可能或可能不是相关的。这种波形多样性提供了MIMO通信的增强功能和性能提高。许多研究论文已经提出了不同的束形策略方法。我们预计，我们的研究将为MIMO通信系统 WITH PLANAR ARRAYS 的不同束形策略的性能提供有价值的发现。我们将使用基于协方差的MIMO通信波形方法来研究这些星座的3D束 Pattern。使用MATLAB仿真来分析和评估这些方法的性能。
Fast Ray-Tracing-Based Precise Underwater Acoustic Localization without Prior Acknowledgment of Target Depth
methods: 我们提出了一种Iterative Ray Tracing 3D Underwater Localization（IRTUL）方法，用于补偿层次质量的影响。我们首先 derivate了信号路径为гляancing角度函数，然后证明信号传播时间和水平传播距离是初始折射角度的 monotonic 函数，从而实现快速的射线跟踪。此外，我们还提出了一种音速profile（SVP）简化方法，以降低射线跟踪的计算成本。
results: 实验结果表明，IRTUL方法可以减少深度方向的距离偏差，并提高了平均精度约3米compared to地理位置模型。此外，简化的SVP方法可以在实时性方面减少精度损失，即使在使用时间平均损失低于0.2米。Abstract
Underwater localization is of great importance for marine observation and building positioning, navigation, timing (PNT) systems that could be widely applied in disaster warning, underwater rescues and resources exploration. The uneven distribution of underwater sound velocity poses great challenge for precise underwater positioning. The current soundline correction positioning method mainly aims at scenarios with known target depth. However, for nodes that are non-cooperative nodes or lack of depth information, soundline tracking strategies cannot work well due to nonunique positional solutions. To tackle this issue, we propose an iterative ray tracing 3D underwater localization (IRTUL) method for stratification compensation. To demonstrate the feasibility of fast stratification compensation, we first derive the signal path as a function of glancing angle, and then prove that the signal propagation time and horizontal propagation distance are monotonic functions of the initial grazing angle, so that fast ray tracing can be achieved. Then, we propose an sound velocity profile (SVP) simplification method, which reduces the computational cost of ray tracing. Experimental results show that the IRTUL has the most significant distance correction in the depth direction, and the average accuracy of IRTUL has been improved by about 3 meters compared to localization model with constant sound velocity. Also, the simplified SVP can significantly improve real-time performance with average accuracy loss less than 0.2 m when used for positioning.
摘要
水下Localization对marine observation和建筑位置、导航、时间（PNT）系统的应用非常重要，特别是在紧急警示、水下搜救和资源探索等领域。水下声速的不均分布对精确水下定位 pose 大 Challenge。目前的声线修正定位方法主要针对已知目标深度的场景，但是对于不合作节点或lack of depth information的情况，声线跟踪策略难以实现Unique positional solution。为解决这个问题，我们提出了一种迭代射线跟踪3D水下定位（IRTUL）方法，用于层次补做。首先，我们 derive 声波路径作为 glance angle 函数，并证明声波传播时间和水平传播距离是初始触角 angle 的唯一 monotonic function，从而实现快速射线跟踪。然后，我们提出了一种声速profile（SVP）简化方法，可以减少射线跟踪的计算成本。实验结果表明，IRTUL在深度方向上具有最大的距离 corrections，并且localization模型中的常数声速的精度提高了约3米。此外，简化的SVP可以在实时性方面提供significant improvement， average accuracy loss less than 0.2 m。
Sensing-assisted Accurate and Fast Beam Management for Cellular-connected mmWave UAV Network
results: 比较 conventional 方法，提出的解决方案在IA延迟、关联精度、跟踪误差和通信性能方面表现出色。Abstract
Beam management, including initial access (IA) and beam tracking, is essential to the millimeter-wave Unmanned Aerial Vehicle (UAV) network. However, conventional communication-only and feedback-based schemes suffer a high delay and low accuracy of beam alignment since they only enable the receiver to passively hear the information of the transmitter from the radio domain. This paper presents a novel sensing-assisted beam management approach, the first solution that fully utilizes the information from the visual domain to improve communication performance. We employ both integrated sensing and communication and computer vision techniques and design an extended Kalman filtering method for beam tracking and prediction. Besides, we also propose a novel dual identity association solution to distinguish multiple UAVs in dynamic environments. Real-world experiments and numerical results show that the proposed solution outperforms the conventional methods in IA delay, association accuracy, tracking error, and communication performance.
摘要
beam 管理，包括初始访问（IA）和扫描 beam，对 millimeter 波无人机网络是必需的。然而，传统的通信只和反馈方案受到高延迟和低精度的扫描Alignment的限制，因为它们只允许接收器在电波频谱中接受发送器的信息。本文提出了一种新的感知协助 beam 管理方法，是首个完全利用视觉频谱中的信息提高通信性能的解决方案。我们利用了集成感知和通信技术，并设计了一种扩展 kalman 筛法 для beam 跟踪和预测。此外，我们还提出了一种新的双重标识关系解决方案，以在动态环境中分辨多个无人机。实际实验和数学结果表明，我们的解决方案在IA延迟、关联精度、跟踪错误和通信性能方面都超过了传统方法。
3D terrain mapping and filtering from coarse resolution data cubes extracted from real-aperture 94 GHz radar
results: 研究结果表明，新的处理方法可以生成稳定的点云，即可重复使用不同的点云提取和筛选参数值进行预处理，并且 less sensitive to over-filtering through the point cloud processing workflow。此外，点云不确定性也减少到了约1.5米至3米之间，比其他靠近范围的雷达系统更小。这些结果可以作为未来使用毫米波雷达系统进行地形映射的标准。Abstract
Accurate, high-resolution 3D mapping of environmental terrain is critical in a range of disciplines. In this study, we develop a new technique, called the PCFilt-94 algorithm, to extract 3D point clouds from coarse resolution millimetre-wave radar data cubes and quantify their associated uncertainties. A technique to non-coherently average neighbouring waveforms surrounding each AVTIS2 range profile was developed in order to reduce speckle and was found to reduce point cloud uncertainty by 13% at long range and 20% at short range. Further, a Voronoi-based point cloud outlier removal algorithm was implemented which iteratively removes outliers in a point cloud until the process converges to the removal of 0 points. Taken together, the new processing methodology produces a stable point cloud, which means that: 1) it is repeatable even when using different point cloud extraction and filtering parameter values during pre-processing, and 2) is less sensitive to over-filtering through the point cloud processing workflow. Using an optimal number of Ground Control Points (GCPs) for georeferencing, which was determined to be 3 at close range (<1.5 km) and 5 at long range (>3 km), point cloud uncertainty was estimated to be approximately 1.5 m at 1.5 km to 3 m at 3 km and followed a Lorentzian distribution. These uncertainties are smaller than those reported for other close-range radar systems used for terrain mapping. The results of this study should be used as a benchmark for future application of millimetre-wave radar systems for 3D terrain mapping.
摘要
精确高分辨度三维地形映射是多个领域的关键。本研究中，我们开发了一种新的算法，即PCFilts-94算法，以提取毫米波雷达数据立方体点云和相关的不确定性。为了减少雷达棱镜的影响，我们开发了一种非协调平均邻近波形式的方法，并发现可以降低点云不确定性13%在远距离和20%在近距离。此外，我们实现了基于Voronoi区域的点云异常点除法，这个过程可以逐步除除点云中的异常点，直到 converge to the removal of 0 points。综上所述，新的处理方法可以生成稳定的点云，其特点是：1)可重复性，即在不同的点云提取和筛选参数值时，可以重复获得相同的结果，2) menos sensitive to over-filtering，即点云处理流程中的过滤效果更加稳定。使用最佳的地面控制点数（GCPs）进行地理参考，其值为1.5 km处3个和3 km处5个，点云不确定性约为1.5 m在1.5 km处到3 m在3 km处，遵循lorentzian分布。这些不确定性较小，比其他靠近范围的雷达系统用于地形映射报告的不确定性更小。本研究的结果应该成为未来毫米波雷达系统的3D地形映射应用的标准。
Multi-Satellite Cooperative Networks: Joint Hybrid Beamforming and User Scheduling Design
paper_authors: Xuan Zhang, Shu Sun, Meixia Tao, Qin Huang, Xiaohu Tang
for: The paper is written for a cooperative communication network where multiple low-Earth-orbit satellites provide services for ground users (GUs) at the same time and on the same frequency.
methods: The paper proposes a hybrid beamforming method consisting of analog beamforming for beam alignment and digital beamforming for interference mitigation, as well as a low-complexity heuristic user scheduling algorithm to establish appropriate connections between the satellites and GUs.
results: The proposed joint hybrid beamforming and user scheduling (JHU) scheme is expected to dramatically improve the performance of the multi-satellite cooperative network, and simulations are conducted to compare the proposed schemes with representative baselines and to analyze the key factors influencing the performance of the network.Here is the same information in Simplified Chinese text:
results: 提出的 JHU 方案预计可以帮助提高多卫星协同网络的性能，并通过与代表性基线相比进行 simulations，分析了网络性能的关键因素。Abstract
In this paper, we consider a cooperative communication network where multiple low-Earth-orbit satellites provide services for ground users (GUs) (at the same time and on the same frequency). The multi-satellite cooperative network has great potential for satellite communications due to its dense configuration, extensive coverage, and large spectral efficiency. However, the communication and computational resources on satellites are usually restricted. Therefore, considering the limitation of the on-board radio-frequency chains of satellites, we first propose a hybrid beamforming method consisting of analog beamforming for beam alignment and digital beamforming for interference mitigation. Then, to establish appropriate connections between the satellites and GUs, we propose a low-complexity heuristic user scheduling algorithm which determines the connections according to the total spectral efficiency increment of the multi-satellite cooperative network. Next, considering the intrinsic connection between beamforming and user scheduling, a joint hybrid beamforming and user scheduling (JHU) scheme is proposed to dramatically improve the performance of the multi-satellite cooperative network. In addition to the single-connection scenario, we also consider the multi-connection case using the JHU scheme. Moreover, simulations are conducted to compare the proposed schemes with representative baselines and to analyze the key factors influencing the performance of the multi-satellite cooperative network.
摘要
在这篇论文中，我们考虑了多颗低地球轨道卫星协作网络，这些卫星为地面用户（GU）提供服务（同时，在同一频率上）。这种多卫星协作网络具有密集配置、广泛覆盖和大 spectral efficiency，但卫星上的通信和计算资源受限。因此，我们首先提出了一种混合扫描方法，其中analog扫描用于杆位定位，而数字扫描用于干扰降低。然后，为建立多卫星协作网络中的合适连接，我们提出了一种低复杂度的冒险用户调度算法，该算法根据多卫星协作网络的总spectral efficiency增量确定连接。接着，我们考虑了扫描和用户调度之间的内在关系，并提出了一种结合扫描和用户调度的共同方案（JHU），以显著提高多卫星协作网络的性能。此外，我们还考虑了多连接情况下的JHU方案。此外，我们进行了对基eline的比较和分析，以分析多卫星协作网络的性能关键因素。
Channel-robust Automatic Modulation Classification Using Spectral Quotient Cumulants
paper_authors: Sai Huang, Yuting Chen, Jiashuo He, Shuo Chang, Zhiyong Feng for:The paper is written for proposing a channel-robust modulation classification framework for orthogonal frequency division multiplexing (OFDM) systems, which can mitigate the adverse effects of multipath channel and improve the classification accuracy.methods:The proposed method uses spectral quotient cumulants (SQCs) extracted from the filtered spectral quotient (SQ) sequence as the inputs to train an artificial neural network (ANN) classifier. The method also employs an outlier detector to filter the outliers in the SQ sequence.results:The simulation results show that the proposed SQCC method exhibits classification robustness and superiority under various unknown Rician multipath fading channels, with nearly 90% classification accuracy at the signal to noise ratio (SNR) of 4dB when testing under multiple channels but training under AWGN channel.Abstract
Automatic modulation classification (AMC) is to identify the modulation format of the received signal corrupted by the channel effects and noise. Most existing works focus on the impact of noise while relatively little attention has been paid to the impact of channel effects. However, the instability posed by multipath fading channels leads to significant performance degradation. To mitigate the adverse effects of the multipath channel, we propose a channel-robust modulation classification framework named spectral quotient cumulant classification (SQCC) for orthogonal frequency division multiplexing (OFDM) systems. Specifically, we first transform the received signal to the spectral quotient (SQ) sequence by spectral circular shift division operations. Secondly, an outlier detector is proposed to filter the outliers in the SQ sequence. At last, we extract spectral quotient cumulants (SQCs) from the filtered SQ sequence as the inputs to train the artificial neural network (ANN) classifier and use the trained ANN to make the final decisions. Simulation results show that our proposed SQCC method exhibits classification robustness and superiority under various unknown Rician multipath fading channels compared with other existing methods. Specifically, the SQCC method achieves nearly 90% classification accuracy at the signal to noise ratio (SNR) of 4dB when testing under multiple channels but training under AWGN channel.
摘要
自动模式分类（AMC）是确定接收信号中的模式格式，它受到通道效果和噪声的影响。现有大多数研究强调噪声的影响，而忽略了通道效果的影响。然而，多路干扰通道会导致性能下降。为了 mitigate 多路干扰通道的影响，我们提出了一种鲁棒的通道robust模式分类框架，名为спектральquotientcumulant分类（SQCC），用于orthogonal frequency division multiplexing（OFDM）系统。specifically，我们首先将接收信号转换为spectral quotient（SQ）序列，然后提出了一种outlier检测器来过滤SQ序列中的异常值。最后，我们从过滤后的SQ序列提取spectral quotientcumulants（SQCs）作为人工神经网络（ANN）分类器的输入，并使用已经训练的ANN来做最终的决定。 simulation results show that our proposed SQCC method exhibits robustness and superiority under various unknown Rician multipath fading channels compared with other existing methods. Specifically, the SQCC method achieves nearly 90% classification accuracy at the signal to noise ratio（SNR）of 4dB when testing under multiple channels but training under AWGN channel.
On the Capacity of Reconfigurable Intelligence Surface: the Sparse Channel Case
results: 论文表明，在RIS反射频谱中支持高级传输更加困难，并且提出了一种基于稀畴性的MIMO通信方法来解决这个问题。Abstract
Reconfigurable intelligent surface (RIS) is an important candidate technology for 6G. We provide an analysis of RIS-assisted MIMO communication in sparse channel typically found in the mmW or THz range. By exploring the sparse property, we maximize the capacity in the singular space of the channel and developed efficient algorithms for SU-MIMO or DL MU-MIMO. We also proved it is more difficult to support high rank transmission in the RIS reflection channel than in the traditional MIMO channel.
摘要
<>重配置智能表面（RIS）是6G技术的重要候选人。我们对RIS协助MIMO通信在罕见频谱中进行分析，通常发生在mmWave或THz范围内。通过探索罕见性，我们最大化了频谱空间中的容量，并开发了高效的SU-MIMO或DL MU-MIMO算法。此外，我们证明了在RIS反射频谱中支持高级传输比traditional MIMO频谱更加困难。[/INST0] Here's the translation of the text into Traditional Chinese:<>重配置智能表面（RIS）是6G技术的重要候选人。我们对RIS协助MIMO通信在罕见频范围中进行分析，通常发生在mmWave或THz范围内。通过探索罕见性，我们最大化了频范围空间中的容量，并开发了高效的SU-MIMO或DL MU-MIMO算法。此外，我们证明了在RIS反射频范围中支持高级传输比traditional MIMO频范围更加困难。