results: 我们的 simulations 表明，我们的方法在精度和运行时间两个方面与先前的工作相比，有更高的性能。我们归因此于解决空间减少和去噪效果。Abstract
This paper studies the problem of Kronecker-structured sparse vector recovery from an underdetermined linear system with a Kronecker-structured dictionary. Such a problem arises in many real-world applications such as the sparse channel estimation of an intelligent reflecting surface-aided multiple-input multiple-output system. The prior art only exploits the Kronecker structure in the support of the sparse vector and solves the entire linear system together leading to high computational complexity. Instead, we break down the original sparse recovery problem into multiple independent sub-problems and solve them individually. We obtain the sparse vector as the Kronecker product of the individual solutions, retaining its structure in both support and nonzero entries. Our simulations demonstrate the superior performance of our methods in terms of accuracy and run time compared with the existing works, using synthetic data and the channel estimation application. We attribute the low run time to the reduced solution space due to the additional structure and improved accuracy to the denoising effect owing to the decomposition step.
摘要
In contrast, our approach breaks down the original sparse recovery problem into multiple independent sub-problems and solves them individually. We obtain the sparse vector as the Kronecker product of the individual solutions, retaining its structure in both support and nonzero entries. Our simulations show that our methods outperform existing works in terms of accuracy and run time, using synthetic data and the channel estimation application. We attribute the low run time to the reduced solution space due to the additional structure and improved accuracy to the denoising effect of the decomposition step.
Adaptive Quantization for Key Generation in Low-Power Wide-Area Networks
results: 实验结果表明，对于 LoRa 设备，我们的自适应量化方案可以与对比方法（差分量化和固定量化）相比，提高 KGR 的表现，最高可以达到 2.35 倍和 1.51 倍的提升。Abstract
Physical layer key generation based on reciprocal and random wireless channels has been an attractive solution for securing resource-constrained low-power wide-area networks (LPWANs). When quantizing channel measurements, namely received signal strength indicator (RSSI), into key bits, the existing works mainly adopt fixed quantization levels and guard band parameters, which fail to fully extract keys from RSSI measurements. In this paper, we propose a novel adaptive quantization scheme for key generation in LPWANs, taking LoRa as a case study. The proposed adaptive quantization scheme can dynamically adjust the quantization parameters according to the randomness of RSSI measurements estimated by Lempel-Ziv complexity (LZ76), while ensuring a predefined key disagreement ratio (KDR). Specifically, our scheme uses pre-trained linear regression models to determine the appropriate quantization level and guard band parameter for each segment of RSSI measurements. Moreover, we propose a guard band parameter calibration scheme during information reconciliation during real-time key generation operation. Experimental evaluations using LoRa devices show that the proposed adaptive quantization scheme outperforms the benchmark differential quantization and fixed quantization with up to 2.35$\times$ and 1.51$\times$ key generation rate (KGR) gains, respectively.
摘要
物理层密钥生成基于相互反射和随机无线通道已成为优化资源充足低功率宽域网络（LPWAN）的一个吸引人的解决方案。当量化通道测量值（RSSI）为密钥位时，现有的工作主要采用固定量化水平和保障带参数，这些参数不足以完全从RSSI测量值中提取密钥。在本文中，我们提出了一种新的自适应量化方案，用于LPWAN中的密钥生成，具体来说是通过Lempel-Ziv复杂度（LZ76）来估计RSSI测量值的随机性，并保证一定的密钥分歧率（KDR）。specifically，我们的方案使用预训练的线性回归模型来确定每个RSSI测量值段的合适的量化水平和保障带参数。此外，我们还提出了在实时密钥生成过程中进行信息重新协调的保射参数calibration方案。实验使用LoRa设备显示，我们的自适应量化方案与参考 differential量化和固定量化相比，可以获得最高达2.35倍和1.51倍的密钥生成速率（KGR）提升。
Exploiting Semantic Localization in Highly Dynamic Wireless Networks Using Deep Homoscedastic Domain Adaptation
results: 本研究通过多任务深度适应（DA）技术，使用有限多个标注样本和大量无标注样本进行地点定位，并提出了scenario适应学习策略，以确保efficient表示学习和成功的知识传递。此外，本研究还使用 bayesian 理论来模型uncertainty weights的重要性，从而降低了时间consuming的参数finetuning。Abstract
Localization in GPS-denied outdoor locations, such as street canyons in an urban or metropolitan environment, has many applications. Machine Learning (ML) is widely used to tackle this critical problem. One challenge lies in the mixture of line-of-sight (LOS), obstructed LOS (OLOS), and non-LOS (NLOS) conditions. In this paper, we consider a semantic localization that treats these three propagation conditions as the ''semantic objects", and aims to determine them together with the actual localization, and show that this increases accuracy and robustness. Furthermore, the propagation conditions are highly dynamic, since obstruction by cars or trucks can change the channel state information (CSI) at a fixed location over time. We therefore consider the blockage by such dynamic objects as another semantic state. Based on these considerations, we formulate the semantic localization with a joint task (coordinates regression and semantics classification) learning problem. Another problem created by the dynamics is the fact that each location may be characterized by a number of different CSIs. To avoid the need for excessive amount of labeled training data, we propose a multi-task deep domain adaptation (DA) based localization technique, training neural networks with a limited number of labeled samples and numerous unlabeled ones. Besides, we introduce novel scenario adaptive learning strategies to ensure efficient representation learning and successful knowledge transfer. Finally, we use Bayesian theory for uncertainty modeling of the importance weights in each task, reducing the need for time-consuming parameter finetuning; furthermore, with some mild assumptions, we derive the related log-likelihood for the joint task and present the deep homoscedastic DA based localization method.
摘要
本文研究用机器学习（ML）在无GPS的户外场景中进行地点地理位置的定位。这些场景包括城市街区的封闭环境，其中存在多种propagation condition，如直接视线（LOS）、受阻视线（OLOS）和非直接视线（NLOS）等。本文提出一种 semantics localization，将这三种propagation condition treated为 semantics objects，并将其与实际地理位置一起确定，以提高精度和可靠性。此外，这些propagation condition是高度动态的，因为卡车或卡车可以在fixed location上时间上对通信状态信息（CSI）进行阻挡。因此，我们将阻挡这些动态对象作为另一种semantic state来考虑。基于以上考虑，我们将semantic localization定义为一个联合任务（coordinates regression和semantics classification）学习问题。此外，由于每个地点可能有多个CSIs，我们提出一种多任务深度适应（DA）基本地址技术，通过使用有限量的标注样本和大量的无标注样本来训练神经网络。此外，我们还引入了一些novel scenario adaptive learning strategy来保证效率的表征学习和成功的知识传递。最后，我们使用 bayesian 理论来模型 uncertainty weight的importance，减少需要时间consuming的参数微调; 此外，在某些轻微的假设下，我们Derive the related log-likelihood for the joint task, and present the deep homoscedastic DA based localization method.
Sparse Millimeter Wave Channel Estimation From Partially Coherent Measurements
results: 我们通过数值分析表明，我们的算法可以在较低的复杂性下高精度地估计通道。Abstract
This paper develops a channel estimation technique for millimeter wave (mmWave) communication systems. Our method exploits the sparse structure in mmWave channels for low training overhead and accounts for the phase errors in the channel measurements due to phase noise at the oscillator. Specifically, in IEEE 802.11ad/ay-based mmWave systems, the phase errors within a beam refinement protocol packet are almost the same, while the errors across different packets are substantially different. Consequently, standard sparsity-aware algorithms, which ignore phase errors, fail when channel measurements are acquired over multiple beam refinement protocol packets. We present a novel algorithm called partially coherent matching pursuit for sparse channel estimation under practical phase noise perturbations. Our method iteratively detects the support of sparse signal and employs alternating minimization to jointly estimate the signal and the phase errors. We numerically show that our algorithm can reconstruct the channel accurately at a lower complexity than the benchmarks.
摘要
The proposed algorithm, called partially coherent matching pursuit, iteratively detects the support of the sparse signal and employs alternating minimization to jointly estimate the signal and the phase errors. The algorithm is designed to handle practical phase noise perturbations and can accurately reconstruct the channel at a lower complexity than the benchmarks.Here is the text in Simplified Chinese:这篇论文提出了一种渠道估计技术 для毫米波通信系统，该技术利用毫米波通道的稀疏结构来减少训练负担，同时考虑振荡器内的频率噪声对渠道测量的影响。具体来说，在IEEE 802.11ad/ay基于毫米波系统中，内部的振荡器频率噪声对同一个扫描射频 packet 的频率错误是非常相似的，而不同包的频率错误则是非常不同的。因此，标准的稀疏意识算法，忽略了频率错误，在多个扫描射频 packet 上不能正确地估计渠道。我们提出了一种新的算法，called partially coherent matching pursuit，该算法 iteratively 检测稀疏信号的支持，并使用交互式最小化来联合估计信号和频率错误。我们numerically 表明，我们的算法可以在较低的复杂性下准确地重建渠道。
Quality of Service-Constrained Online Routing in High Throughput Satellites
paper_authors: Olivier Bélanger, Olfa Ben Yahia, Stéphane Martel, Antoine Lesage-Landry, Gunes Karabulut Kurt for: 这篇论文旨在解决高通信卫星（HTS）内部网络的优化问题，以实现高速数据传输和保持质量服务（QoS）标准。methods: 该论文提出了一种在线优化流量分配和计划方法，基于多品质流模型（MPC）的预测控制技术，以适应HTS数据流的变化和不确定性。results: 对于 numerical simulations，该方法与预先知道的优质方法相比，能够实现几乎与优质方法相当的性能，证明了其有效性和适应性。Abstract
High Throughput Satellites (HTSs) outpace traditional satellites due to their multi-beam transmission. The rise of low Earth orbit mega constellations amplifies HTS data rate demands to terabits/second with acceptable latency. This surge in data rate necessitates multiple modems, often exceeding single device capabilities. Consequently, satellites employ several processors, forming a complex packet-switch network. This can lead to potential internal congestion and challenges in adhering to strict quality of service (QoS) constraints. While significant research exists on constellation-level routing, a literature gap remains on the internal routing within a singular HTS. The intricacy of this internal network architecture presents a significant challenge to achieve high data rates. This paper introduces an online optimal flow allocation and scheduling method for HTSs. The problem is treated as a multi-commodity flow instance with different priority data streams. An initial full time horizon model is proposed as a benchmark. We apply a model predictive control (MPC) approach to enable adaptive routing based on current information and the forecast within the prediction time horizon while allowing for deviation of the latter. Importantly, MPC is inherently suited to handle uncertainty in incoming flows. Our approach minimizes packet loss by optimally and adaptively managing the priority queue schedulers and flow exchanges between satellite processing modules. Central to our method is a routing model focusing on optimal priority scheduling to enhance data rates and maintain QoS. The model's stages are critically evaluated, and results are compared to traditional methods via numerical simulations. Through simulations, our method demonstrates performance nearly on par with the hindsight optimum, showcasing its efficiency and adaptability in addressing satellite communication challenges.
摘要
高通过put Satellites (HTSs) 的传输速率比传统卫星更快，因为它们使用多个扫描。随着低地球轨道巨型卫星的出现，HTS 数据率需求增加到 Terra bits/秒，同时保持可接受的延迟。这种增加的数据率使得多个模式、常常超过单个设备的能力。因此，卫星通常使用多个处理器，形成复杂的包队列网络。这可能会导致内部塞突和遵循严格的服务质量（QoS）约束的挑战。虽然关于卫星群 constellation 级别的路由研究已经有很多，但是关于单个 HTS 内部路由的研究还存在一个知识空白。卫星内部网络的复杂性提出了高达数据率的挑战。本文介绍了一种在 HTS 中线上优化流量分配和调度方法。该问题被视为多商品流 instances 中的一个，其中有不同优先级数据流。我们提出了一个全时间轴模型作为参考。我们采用了预测控制（MPC）方法，以适应现有信息和预测时间 horizon 内的变化。MPC 自然地能够处理入流的不确定性。我们的方法可以最小化包产生损失，通过优化优先级调度和卫星处理模块之间的流体换来实现高达数据率和维护 QoS。中心于我们的方法的是一种专注于优化优先级调度，以提高数据率和维护 QoS。模型的阶段得到了严格的评估，并与传统方法进行比较。通过 simulations，我们的方法可以与后看 optimum 的性能相似，这显示了它的效率和适应性。
Proactive Monitoring via Jamming in Fluid Antenna Systems
results: 实验结果表明，提出的方案可以较 Convention benchmark 高效地提高监测性能。Abstract
This paper investigates the efficacy of utilizing fluid antenna system (FAS) at a legitimate monitor to oversee suspicious communication. The monitor switches the antenna position to minimize its outage probability for enhancing the monitoring performance. Our objective is to maximize the average monitoring rate, whose expression involves the integral of the first-order Marcum $Q$ function. The optimization problem, as initially posed, is non-convex owing to its objective function. Nevertheless, upon substituting with an upper bound, we provide a theoretical foundation confirming the existence of a unique optimal solution for the modified problem, achievable efficiently by the bisection search method. Furthermore, we also introduce a locally closed-form optimal resolution for maximizing the average monitoring rate. Empirical evaluations confirm that the proposed schemes outperform conventional benchmarks considerably.
摘要
Simplified Chinese:这篇论文研究了使用流体天线系统（FAS）在合法监控器上监测异常通信的效果。监控器通过调整天线位置来最小化监测损失的概率，以提高监测性能。我们的目标是最大化平均监测率，其表达式包括首频 Marcum $Q$ 函数的积分。然而，原始优化问题是非凸的，但我们通过substituted an upper bound提供了一个理论基础，证明了优化问题的唯一优解存在。此外，我们还引入了一个本地关闭形式的优化解决方案，以最大化平均监测率。实验证明，我们的提议方案在与传统标准相比较显著地出performances。
Symbol-Level Precoding for Average SER Minimization in Multiuser MISO Systems
paper_authors: Yafei Wang, Hongwei Hou, Wenjin Wang, Xinping Yi
for: investigate symbol-level precoding (SLP) for high-order quadrature amplitude modulation (QAM) to minimize average symbol error rate (SER) and improve full signal-to-noise ratio (SNR) ranges.
methods: construct SER expression, formulate problem of average SER minimization subject to total transmit power constraint, and propose double-space alternating optimization (DSAO) algorithm to optimize transmitted signal and rescaling factor on orthogonal Stiefel manifold and Euclidean spaces, respectively.
results: propose a block transmission scheme to keep rescaling factor constant within a block, and demonstrate significant performance advantage over existing state-of-the-art SLP schemes through simulation results.Abstract
This paper investigates symbol-level precoding (SLP) for high-order quadrature amplitude modulation (QAM) aimed at minimizing the average symbol error rate (SER), leveraging both constructive interference (CI) and noise power to gain superiority in full signal-to-noise ratio (SNR) ranges. We first construct the SER expression with respect to the transmitted signal and the rescaling factor, based on which the problem of average SER minimization subject to total transmit power constraint is further formulated. Given the non-convex nature of the objective, solving the above problem becomes challenging. Due to the differences in constraints between the transmit signal and the rescaling factor, we propose the double-space alternating optimization (DSAO) algorithm to optimize the two variables on orthogonal Stiefel manifold and Euclidean spaces, respectively. To facilitate QAM demodulation instead of affording impractical signaling overhead, we further develop a block transmission scheme to keep the rescaling factor constant within a block. Simulation results demonstrate that the proposed SLP scheme exhibits a significant performance advantage over existing state-of-the-art SLP schemes.
摘要
Here is the translation in Simplified Chinese:这篇论文研究了使用高阶 quadrature amplitude modulation (QAM) 的 symbol-level precoding (SLP)，以最小化平均符号错误率 (SER)，利用构建性干扰 (CI) 和噪声功率。我们首先 derive SER 表达式，基于这些表达式，我们进一步形式化了在全信号响应率 (SNR) 范围内的平均 SER 最小化问题，并且采用了 double-space alternating optimization (DSAO) 算法来优化两个变量。为了使 QAM 模测可行，我们采用了块传输方案，以保持块内的扩大因子不变。Results show that the proposed SLP scheme outperforms existing state-of-the-art SLP schemes.
IRS Assisted Federated Learning A Broadband Over-the-Air Aggregation Approach
results: 研究人员通过对MNIST数据集进行 simulate，并分析了两种基于节点选择和重量选择的模型集成方法的性能。结果显示， weight-selection 方法可以提高学习性能，而节点选择方法的性能与选择的边缘节点数量有关。Abstract
We consider a broadband over-the-air computation empowered model aggregation approach for wireless federated learning (FL) systems and propose to leverage an intelligent reflecting surface (IRS) to combat wireless fading and noise. We first investigate the conventional node-selection based framework, where a few edge nodes are dropped in model aggregation to control the aggregation error. We analyze the performance of this node-selection based framework and derive an upper bound on its performance loss, which is shown to be related to the selected edge nodes. Then, we seek to minimize the mean-squared error (MSE) between the desired global gradient parameters and the actually received ones by optimizing the selected edge nodes, their transmit equalization coefficients, the IRS phase shifts, and the receive factors of the cloud server. By resorting to the matrix lifting technique and difference-of-convex programming, we successfully transform the formulated optimization problem into a convex one and solve it using off-the-shelf solvers. To improve learning performance, we further propose a weight-selection based FL framework. In such a framework, we assign each edge node a proper weight coefficient in model aggregation instead of discarding any of them to reduce the aggregation error, i.e., amplitude alignment of the received local gradient parameters from different edge nodes is not required. We also analyze the performance of this weight-selection based framework and derive an upper bound on its performance loss, followed by minimizing the MSE via optimizing the weight coefficients of the edge nodes, their transmit equalization coefficients, the IRS phase shifts, and the receive factors of the cloud server. Furthermore, we use the MNIST dataset for simulations to evaluate the performance of both node-selection and weight-selection based FL frameworks.
摘要
我们考虑了一种宽带无线通信 empowered 模型聚合方法 для无线联合学习（FL）系统，并提议利用智能反射表面（IRS）来抗衰减和噪声。我们首先investigate了传统的节点选择基础框架，其中一些边节点被排除在模型聚合中来控制聚合错误。我们分析了这种节点选择基础框架的性能，并 derivated一个上限 bound的性能损失，该损失与选择的边节点相关。然后，我们寻求通过最小化模型聚合中的均方差（MSE）来实现 global 梯度参数与实际接收的梯度参数之间的均方差最小化。为此，我们采用矩阵提升技术和差分 convex 编程，将问题转化为一个convex问题，并使用存储库中的解决方案。为了提高学习性能，我们进一步提议一种weight-selection based FL框架。在这种框架中，我们为每个边节点分配一个适当的weight coefficient，以便在模型聚合中减少聚合错误，即不需要对接收到的本地梯度参数进行幂等匹配。我们还分析了weight-selection based FL框架的性能，并 derivated一个上限 bound的性能损失，然后通过最小化MSE来实现模型聚合中的均方差最小化。此外，我们使用 MNIST 数据集进行实验来评估两种 FL 框架的性能。
Integrated Sensing and Communication enabled Doppler Frequency Shift Estimation and Compensation
paper_authors: Jinzhu Jia, Zhiqing Wei, Ruiyun Zhang, Lin Wang
for: 这篇论文是为了解决高速车辆网络中 millimeter wave 技术导致的严重 Doppler Frequency Shift (DFS) 问题，以提高通信性能。
methods: 本论文提出了一个 Integrated Sensing and Communication (ISAC) 实现 DFS 估计和补偿算法，包括对 DFS 进行粗略估计和补偿、使用设计的 preamble 序列进行精确估计和补偿，以及适应式 DFS 估计器以减少计算复杂度。
results: 比较traditional DFS 估计算法，提案的算法在 bit error rate 和平均方差Error 性能上显示出改善。Abstract
Despite the millimeter wave technology fulfills the low-latency and high data transmission, it will cause severe Doppler Frequency Shift (DFS) for high-speed vehicular network, which tremendously damages the communication performance. In this paper, we propose an Integrated Sensing and Communication (ISAC) enabled DFS estimation and compensation algorithm. Firstly, the DFS is coarsely estimated and compensated using radar detection. Then, the designed preamble sequence is used to accurately estimate and compensate DFS. In addition, an adaptive DFS estimator is designed to reduce the computational complexity. Compared with the traditional DFS estimation algorithm, the improvement of the proposed algorithm is verified in bit error rate and mean square error performance by simulation results.
摘要
尽管毫米波技术实现了低延迟和高数据传输，但它会导致高速交通网络中严重的多普勒频率偏移（DFS），从而极大地损害通信性能。在这篇论文中，我们提出了一种结合探测和通信（ISAC）能力的DFS估算和补偿算法。首先，通过雷达探测来粗略地估算并补偿DFS。然后，采用设计的首部序列来精度地估算和补偿DFS。此外，我们还设计了一种适应式DFS估算器，以降低计算复杂性。与传统的DFS估算算法相比，我们的提案的改进被证明通过实验结果的比特错误率和均方差性能。
paper_authors: Leonhard Grosse, Sara Saeidian, Tobias Oechtering
for: 本文研究了在不可靠第三方party发布数据时，如何保护数据隐私。
methods: 本文使用了随机性加载到数据点，以降低数据的有用性。
results: 研究发现，随机response机制可以实现本地均衡隐私，并且可以通过 convex 分析获得一些关键的关键解。Abstract
Data publishing under privacy constraints can be achieved with mechanisms that add randomness to data points when released to an untrusted party, thereby decreasing the data's utility. In this paper, we analyze this privacy-utility tradeoff for the pointwise maximal leakage privacy measure and a general class of convex utility functions. Pointwise maximal leakage (PML) was recently proposed as an operationally meaningful privacy measure based on two equivalent threat models: An adversary guessing a randomized function and an adversary aiming to maximize a general gain function. We study the behavior of the randomized response mechanism designed for local differential privacy under different prior distributions of the private data. Motivated by the findings of this analysis, we derive several closed-form solutions for the optimal privacy-utility tradeoff in the presented PML context using tools from convex analysis. Finally, we present a linear program that can compute optimal mechanisms for PML in a general setting.
摘要
<>传输数据以遵循隐私限制可以通过添加随机性到数据点来实现，从而降低数据的使用价值。在这篇论文中，我们分析了这种隐私-使用价值贸易的关系，使用点最大泄露隐私度量（PML）和一类凸Utility函数。PML是最近提出的一种操作可能性的隐私度量，基于两种等价威胁模型：敌方猜测一个随机函数，以及敌方尝试最大化一个通用获得函数。我们研究了随机响应机制在本地差分隐私下的不同先前分布的私人数据的行为。受此分析的结果启发，我们 deriv了一些关闭形式的解决方案，用于PML上的优化隐私-使用价值贸易。最后，我们提出了一个可以计算PML上优化机制的线性程序。Note: "随机函数" in the original text is translated as "随机性" in Simplified Chinese, which is a more common term used in the field.
A Unified Algorithmic Framework for Dynamic Compressive Sensing
results: 在实际应用场景，如无线通信中的动态通道跟踪，该框架比既有的DCS算法表现出更高的性能。Abstract
We propose a unified dynamic tracking algorithmic framework (PLAY-CS) to reconstruct signal sequences with their intrinsic structured dynamic sparsity. By capitalizing on specific statistical assumptions concerning the dynamic filter of the signal sequences, the proposed framework exhibits versatility by encompassing various existing dynamic compressive sensing (DCS) algorithms. This is achieved through the incorporation of a newly proposed Partial-Laplacian filtering sparsity model, tailored to capture a more sophisticated dynamic sparsity. In practical scenarios such as dynamic channel tracking in wireless communications, the framework demonstrates enhanced performance compared to existing DCS algorithms.
摘要
我们提出一个统一的动态跟踪算法框架（PLAY-CS），用于重建信号序列的内在结构化动态稀烈性。通过利用信号序列动态滤波器的特定统计假设，我们的框架能够展示多样性，包括不同的动态压缩感知（DCS）算法。这是通过 newly proposed partial-laplace 滤波稀烈性模型来实现的，这种模型用于捕捉更复杂的动态稀烈性。在无线通信中的实际应用场景中，我们的框架可以比既有的 DCS 算法表现更好。Note: The translation is in Simplified Chinese, which is the standard writing system used in mainland China. If you prefer Traditional Chinese, please let me know and I can provide the translation in that format as well.
Input-Output Relation and Low-Complexity Receiver Design for CP-OTFS Systems with Doppler Squint
results: simulations 表明，DSE 对 OTFS 系统的性能有重要影响，而提posed 的低复杂度接收器设计可以考虑 DSE，并有显著的性能提升。Abstract
In orthogonal time frequency space (OTFS) systems, the impact of frequency-dependent Doppler which is referred to as the Doppler squint effect (DSE) is accumulated through longer duration, whose negligence has prevented OTFS systems from exploiting the performance superiority. In this paper, practical OFDM system using cyclic prefix time guard interval (CP-OFDM)-based OTFS systems with DSE are adopted. Cyclic prefix (CP) length is analyzed while the input-output relation considering DSE is derived. By deploying two prefix OFDM symbols, the channel estimation can be easily divided into three parts as delay detection, Doppler extraction and gain estimation. The linear equalization scheme is adopted taking the block diagonal property of the channel matrix into account, which completes the low-complexity receiver design. Simulation results confirm the significance of DSE and the considerable performance of the proposed low-complexity receiver scheme considering DSE.
摘要
在正交时频空间（OTFS）系统中，频率相关的多普勒效应（DSE）的影响会随着时间的推移而受拥，这种忽略会导致OTFS系统无法实现性能优势。本文提出了基于CP-OFDM的OTFS系统，其中CP长度进行分析，并 derivation of the input-output relation considering DSE。通过分配两个prefix OFDM符号，渠道估计可以被简单地分解为三部分：延迟探测、多普勒提取和增强估计。采用了线性平衡方案，利用通道矩阵的块对称性，实现了低复杂度接收器设计。实验结果证明了DSE的重要性以及提议的低复杂度接收器计划的出色表现。
Integrated Sensing and Communication enabled Multiple Base Stations Cooperative Sensing Towards 6G
for: sixth-generation (6G) mobile communication systems, such as smart city and autonomous driving
methods: multi-BS cooperative sensing, unified ISAC performance metrics, ISAC signal design and optimization, interference management, cooperative sensing algorithms
results: breaking the limitation of single-BS sensing, establishing intelligent infrastructures connecting physical and cyber space, ushering the era of 6GAbstract
Driven by the intelligent applications of sixth-generation (6G) mobile communication systems such as smart city and autonomous driving, which connect the physical and cyber space, the integrated sensing and communication (ISAC) brings a revolutionary change to the base stations (BSs) of 6G by integrating radar sensing and communication in the same hardware and wireless resource. However, with the requirements of long-range and accurate sensing in the applications of smart city and autonomous driving, the ISAC enabled single BS still has a limitation in the sensing range and accuracy. With the networked infrastructures of mobile communication systems, multi-BS cooperative sensing is a natural choice satisfying the requirement of long-range and accurate sensing. In this article, the framework of multi-BS cooperative sensing is proposed, breaking through the limitation of single-BS sensing. The enabling technologies, including unified ISAC performance metrics, ISAC signal design and optimization, interference management, cooperative sensing algorithms, are introduced in details. The performance evaluation results are provided to verify the effectiveness of multi-BS cooperative sensing schemes. With ISAC enabled multi-BS cooperative sensing (ISAC-MCS), the intelligent infrastructures connecting physical and cyber space can be established, ushering the era of 6G promoting the intelligence of everything.
摘要
驱动了六代移动通信系统（6G）的智能应用，如智能城市和自动驾驶，这些应用连接了物理空间和虚拟空间，因此集成感知和通信（ISAC）在6G基站（BS）中带来了革命性的变革。然而，在智能城市和自动驾驶应用中需要覆盖较长范围和精度高的感知，ISAC启用的单BS仍有限制的感知范围和精度。基于移动通信系统的网络基础设施，多BS合作感知是一个自然的选择，满足覆盖较长范围和精度高的感知需求。本文提出了多BS合作感知框架，突破单BS感知的限制。本文还介绍了实现多BS合作感知的关键技术，包括统一ISAC性能指标、ISAC信号设计优化、干扰管理和合作感知算法。本文还提供了性能评估结果，证明了多BS合作感知方案的有效性。通过ISAC启用的多BS合作感知（ISAC-MCS），智能基础设施可以建立，推动6G时代，智能化 Everything。
Time and Frequency Offset Estimation and Intercarrier Interference Cancellation for AFDM Systems
methods: 这篇论文提出了两种最大 LIKELIHOOD（ML）估计器：一个 JOINT ML 估计器，通过比较样本之间的相似性来评估到来访时间和频率偏移；另一个是 Stepwise ML 估计器，可以降低复杂度。这两种估计器都利用 AFDM symbol 中内含的双极几何资讯，无需额外的导频。
results: numerically 的结果显示，提出的时间和频率偏移估计准确性和 mirror-mapping 基本帧调制可以实现 AFDM 系统中的可靠通信。Abstract
Affine frequency division multiplexing (AFDM) is an emerging multicarrier waveform that offers a potential solution for achieving reliable communication for time-varying channels. This paper proposes two maximum likelihood (ML) estimators of symbol time offset and carrier frequency offset for AFDM systems. The joint ML estimator evaluates the arrival time and frequency offset by comparing the correlations of samples. Moreover, we propose the stepwise ML estimator to reduce the complexity. The proposed estimators exploit the redundant information contained within the chirp-periodic prefix inherent in AFDM symbols, thus dispensing with any additional pilots. To further mitigate the intercarrier interference resulting from the residual frequency offset, we design a mirror-mappingbased scheme for AFDM systems. Numerical results verify the effectiveness of the proposed time and frequency offset estimation criteria and the mirror-mapping-based modulation for AFDM systems.
摘要
《 Affine 频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通频率分多普通
Edge Cloud Collaborative Stream Computing for Real-Time Structural Health Monitoring
results: 根据先前的评估结果，ECStream可以有效地对带宽和终端 оператор处理延迟进行平衡，将带宽使用率降低到73.01%，并将终端operator computation延迟降低到34.08%的水平。Abstract
Structural Health Monitoring (SHM) is crucial for the safety and maintenance of various infrastructures. Due to the large amount of data generated by numerous sensors and the high real-time requirements of many applications, SHM poses significant challenges. Although the cloud-centric stream computing paradigm opens new opportunities for real-time data processing, it consumes too much network bandwidth. In this paper, we propose ECStream, an Edge Cloud collaborative fine-grained stream operator scheduling framework for SHM. We collectively consider atomic and composite operators together with their iterative computability to model and formalize the problem of minimizing bandwidth usage and end-to-end operator processing latency. Preliminary evaluation results show that ECStream can effectively balance bandwidth usage and end-to-end operator computation latency, reducing bandwidth usage by 73.01% and latency by 34.08% on average compared to the cloud-centric approach.
摘要
STRUCTURAL HEALTH MONITORING (SHM) 是重要的安全和维护基础设施的关键。由于众多感知器件生成的大量数据以及许多应用程序的高实时要求，SHM带来了重大挑战。虽然云计算中心主义思想开启了新的实时数据处理机会，但它占用了过多的网络带宽。在本文中，我们提出了ECStream，一个边缘云集成细致流操作调度框架，用于解决SHM中的带宽使用和终端操作计算延迟问题。我们一起考虑原子和复合运算者的迭代可计算性，以模型和正式化带宽使用和终端操作计算延迟的最佳化问题。初步评估结果表明，ECStream可以有效均衡带宽使用和终端操作计算延迟，减少带宽使用率73.01%，减少平均计算延迟34.08%。
Decentralization of Energy Systems with Blockchain: Bridging Top-down and Bottom-up Management of the Electricity Grid
results: 本文认为，通过使用区块链技术，可以实现分布式能源系统中的端到端交易，并且可以帮助实现现有的中央化操作模式和分布式操作模式之间的协同操作。Abstract
For more than a century, the grid has operated in a centralized top-down fashion. However, as distributed energy resources (DERs) penetration grows, the grid edge is increasingly infused with intelligent computing and communication capabilities. Thus, the bottom-up approach to grid operations inclined toward decentralizing energy systems will likely gain momentum alongside the existing centralized paradigm. Decentralization refers to transferring control and decision-making from a centralized entity (individual, organization, or group thereof) to a distributed network. It is not a new concept - in energy systems context or otherwise. In the energy systems context, however, the complexity of this multifaceted concept increases manifolds due to two major reasons - i) the nature of the commodity being traded (the electricity) and ii) the enormity of the traditional electricity sector's structure that builds, operates, and maintains this capital-intensive network. In this work, we aim to highlight the need for and outline a credible path toward restructuring the current operational architecture of the electricity grid in view of the ongoing decentralization trends with an emphasis on peer-to-peer energy trading. We further introduce blockchain technology in the context of decentralized energy systems problems. We also suggest that blockchain is an effective technology for facilitating the synergistic operations of top-down and bottom-up approaches to grid management.
摘要
Translation notes:* "grid" is translated as "电网" (dian wang)* "centralized" is translated as "中央化" (zhong yang hua)* "decentralized" is translated as "分散化" (fen shi hua)* "bottom-up" is translated as "底层化" (di yan hua)* "top-down" is translated as "顶层化" (ding yan hua)* "peer-to-peer" is translated as "对等" (dui yi)* "blockchain" is translated as "区块链" (qu yu lian)
Hybrid Arrays: How Many RF Chains Are Required to Prevent Beam Squint?
paper_authors: Heedong Do, Namyoon Lee, Robert W. Heath Jr, Angel Lozano
for: 解决 beamforming 中的 beam squint 问题
methods: 使用 hybrid arrays，不需要 downconversion at each element
results: hybrid arrays 可以达到 digital arrays 的性能水平，但需要 exceeds a certain threshold 的数量Here’s the breakdown of each point:1. for: The paper is written to solve the problem of beam squint in beamforming.2. methods: The paper proposes the use of hybrid arrays, which do not require downconversion at each element, to achieve the same performance as digital arrays.3. results: The paper shows that hybrid arrays can achieve the same performance as digital arrays, but with a lower threshold of elements. The result is robust and holds for suboptimum but highly appealing beamspace architectures.Abstract
With increasing frequencies, bandwidths, and array apertures, the phenomenon of beam squint arises as a serious impairment to beamforming. Fully digital arrays with true time delay per antenna element are a potential solution, but they require downconversion at each element. This paper shows that hybrid arrays can perform essentially as well as digital arrays once the number of radio-frequency chains exceeds a certain threshold that is far below the number of elements. The result is robust, holding also for suboptimum but highly appealing beamspace architectures.
摘要