paper_authors: Jasmine Sinanan-Singh, Gabriel L. Mintzer, Isaac L. Chuang, Yuan Liu for: 这个论文的目的是为了探讨量子系统的感测问题，具体来说是使用量子信号处理技术来实现量子感测的最低限制。methods: 这篇论文使用了量子信号处理技术（QSP），将其扩展到混合量子-振荡器系统中，并将其应用于探讨量子感测问题。results: 论文的结果表明，使用QSP技术可以实现量子感测的最低限制，并且可以在单shot情况下达到Heisenberg限制的精度。此外，论文还提出了一种 concatenate 多个 binary 决策来实现参数估计的方法。Abstract
Quantum systems of infinite dimension, such as bosonic oscillators, provide vast resources for quantum sensing. Yet, a general theory on how to manipulate such bosonic modes for sensing beyond parameter estimation is unknown. We present a general algorithmic framework, quantum signal processing interferometry (QSPI), for quantum sensing at the fundamental limits of quantum mechanics, i.e., the Heisenberg sensing limit, by generalizing Ramsey-type interferometry. Our QSPI sensing protocol relies on performing nonlinear polynomial transformations on the oscillator's quadrature operators by generalizing quantum signal processing (QSP) from qubits to hybrid qubit-oscillator systems. We use our QSPI sensing framework to make binary decisions on a displacement channel in the single-shot limit. Theoretical analysis suggests the sensing accuracy given a single-shot qubit measurement can approach the Heisenberg-limit scaling. We further concatenate a series of such binary decisions to perform parameter estimation in a bit-by-bit fashion. Numerical simulations are performed to support these statements. Our QSPI protocol offers a unified framework for quantum sensing using continuous-variable bosonic systems beyond parameter estimation and establishes a promising avenue toward efficient and scalable quantum control and quantum sensing schemes beyond the NISQ era.
摘要
量子系统的无穷维度，如波动器，提供了庞大的量子感知资源。然而，一个涵盖所有bosonic模式的整体理论，用于超出参数估计的感知，仍未知。我们提出了一个通用的算法框架，量子信号处理折射（QSPI），用于量子感知的基础限制，即Heisenberg感知限制，通过普适ramsey-类折射估计。我们的QSPI感知协议基于在hybrid qubit-oscillator系统中实现非线性多项式变换的oscillatorquadrature operator。我们使用QSPI感知框架来在单射shot限制下作出binary决策，并 theoretically analyze the sensing accuracy can approach Heisenberg-limit scaling。我们还将这些binary决策 concatenate在一起，以进行参数估计的bit-by-bit方式。numerical simulations are performed to support these statements. our QSPI protocol provides a unified framework for quantum sensing using continuous-variable bosonic systems beyond parameter estimation and establishes a promising avenue toward efficient and scalable quantum control and quantum sensing schemes beyond the NISQ era.
Cramér-Rao Bounds for the Simultaneous Estimation of Power System Electromechanical Modes and Forced Oscillations
for: 本文derives the Cramér-Rao Bounds (CRB) for simultaneously estimating power system electromechanical modes and forced oscillations (FO).
methods: 本文使用了两种情况：在第一个情况下，仅使用测量系统输出中存在稳态响应的FO来估计模型。在第二个情况下， startup transient of FO 也存在于测量系统输出中。
results: 1) FO参数的CRB不受 startup transient的影响；2) system mode的CRB不受稳态FO的影响；3) system mode的CRB可以通过FO的启动过程来减少。Abstract
In this paper, the Cram\'{e}r-Rao Bounds (CRB) for the simultaneous estimation of power system electromechanical modes and forced oscillations (FO) are derived. Two cases are considered; in the first case only the steady-state response to the FO is present in the measured system output used by estimation algorithms. In the second, the startup transient of the FO is present in addition to the steady-state response. The CRBs are analyzed numerically to explore sensitivities to FO frequency, signal-to-noise ratio (SNR) and observation window length. It is demonstrated that 1) the CRB of FO parameters is not affected by the presence of the transient response, 2) the CRB of the system modes is not affected by the presence of an FO in steady-state and 3) the CRB of the system modes can be drastically reduced by the presence of a FO startup transient.
摘要
在这篇论文中，我们 derive the Cramér-Rao Bounds (CRB) for simultaneously estimating power system electromechanical modes and forced oscillations (FO). 我们考虑了两种情况：在第一种情况下，测量系统输出中只有FO的稳态响应存在，而在第二种情况下， startup 过程中的FO响应也存在。我们 numerically 分析了CRB，并explored its sensitivity to FO frequency, signal-to-noise ratio (SNR)和观测窗口长度。结果表明：1. FO参数的CRB不受 startup 过程的影响。2. 系统模式的CRB不受FO的稳态响应的影响。3. 系统模式的CRB可以通过FO的 startup 过程来减少显著地。
Volumetric 3D Point Cloud Attribute Compression: Learned polynomial bilateral filter for prediction
results: paper 通过对多个 point cloud 数据集进行测试，证明了 PBF 的预测性能超过了基于 MPEG 标准的线性预测器。Abstract
We extend a previous study on 3D point cloud attribute compression scheme that uses a volumetric approach: given a target volumetric attribute function $f : \mathbb{R}^3 \mapsto \mathbb{R}$, we quantize and encode parameters $\theta$ that characterize $f$ at the encoder, for reconstruction $f_{\hat{\theta}(\mathbf(x))$ at known 3D points $\mathbf(x)$ at the decoder. Specifically, parameters $\theta$ are quantized coefficients of B-spline basis vectors $\mathbf{\Phi}_l$ (for order $p \geq 2$) that span the function space $\mathcal{F}_l^{(p)}$ at a particular resolution $l$, which are coded from coarse to fine resolutions for scalability. In this work, we focus on the prediction of finer-grained coefficients given coarser-grained ones by learning parameters of a polynomial bilateral filter (PBF) from data. PBF is a pseudo-linear filter that is signal-dependent with a graph spectral interpretation common in the graph signal processing (GSP) field. We demonstrate PBF's predictive performance over a linear predictor inspired by MPEG standardization over a wide range of point cloud datasets.
摘要
我们推展了之前的研究，使用三维方向云集特征压缩方案，以承载目标三维函数$f:\mathbb{R}^3\mapsto\mathbb{R}$。具体来说，我们在编码器端将函数参数$\theta$逐渐压缩和编码，然后在解码器端使用已知的3D点$\mathbf(x)$进行重建。具体来说，参数$\theta$是B-spline基函数$\mathbf{\Phi}_l$（对应于至少第二阶幂数$p$）所对的压缩系数，这些基函数在特定的分辨率$l$上构成了函数空间$\mathcal{F}_l^{(p)}$。在这个研究中，我们专注于在粗糙对于细节的假设下预测细节对于粗糙的假设。我们利用数据驱动的假设学习方法，从数据中学习一个幂数滤波器（PBF）的参数。PBF是一种 Pseudo-linear filter，它在信号依赖的情况下具有一个图像 спектраль解释，这种解释在图像信号处理（GSP）领域非常普遍。我们在一系列的点云数据上证明了PBF的预测性能，比起基于MPEG标准的直线预测器。
Real-time unobtrusive sleep monitoring of in-patients with affective disorders: a feasibility study
results: 研究发现，使用 Ballistocardiography 测量睡眠质量可以是一种可靠的方法，并且未发现与医疗期长和睡眠时间相关的联系。Abstract
Sleep and mental health are highly related concepts, and it is an important research and clinical priority to understand their interactions. In-bed sensors using ballistocardiography provide the possibility of unobtrusive measurements of sleep. In this study, we examined the feasibility of ballistocardiography in measuring key aspects of sleep in psychiatric in-patients. Specifically, we examined a sample of patients diagnosed with depression and bipolar disorder. The subjective experiences of the researchers conducting the study are explored and descriptive analyses of patient sleep are subsequently presented. The practicalities of using the ballistocardiography device seem to be favourable. There were no apparent issues regarding data quality or data integrity. Of clinical interest, we found no link between length of stay and reduced time in bed (b = -0.06, SE = 0.03, t = -1.76, p = .08). Using ballistocardiography for measurements on in-patients with affective disorders seems to be a feasible approach.
摘要
睡眠和心理健康是高度相关的概念，研究和临床 Priority 是理解它们之间的交互。床上传感器使用球isto cardiography 提供了不侵入性的睡眠测量的可能性。本研究通过对心理病院患者进行评估，评估了球isto cardiography 在诊断抑郁症和跨度症患者中的可行性。研究人员的主观经验和患者睡眠的描述分析后，发现使用球isto cardiography device 的实际问题不大，无 apparent data quality 或数据完整性问题。临床意义上，我们未发现Length of stay 和睡眠时间减少的关系（b = -0.06, SE = 0.03, t = -1.76, p = .08）。使用球isto cardiography 测量心理病院患者的睡眠似乎是一种可行的方法。
Millimeter Wave Thin-Film Bulk Acoustic Resonator in Sputtered Scandium Aluminum Nitride Using Platinum Electrodes
results: 研究发现，使用Pt顶部和底部电极的FBAR可以实现电机学性能（k2）为4.0%，Q因子为116，在13.7GHz的首顺模（S1）频率上；而使用Pt顶部和Al底部电极的FBAR可以实现k2为1.8%，Q因子为94，在61.6GHz的第三顺模（S3）频率上。这些结果表明， même dans la bande de fréquences de l’ordre de 60GHz, les FBAR à ScAlN peuvent atteindre un facteur de qualité s’approchant de 100 avec une fabrication et une conception acoustique/émetteur optimisées.Abstract
This work describes sputtered scandium aluminum nitride (ScAlN) thin-film bulk acoustic resonators (FBAR) at millimeter wave (mmWave) with high quality factor (Q) using platinum (Pt) electrodes. FBARs with combinations of Pt and aluminum (Al) electrodes, i.e., Al top Al bottom, Pt top Al bottom, Al top Pt bottom, and Pt top Pt bottom, are built to study the impact of electrodes on mmWave FBARs. The demonstrated FBAR with Pt top and bottom electrodes achieve electromechanical coupling (k2) of 4.0% and Q of 116 for the first-order symmetric (S1) mode at 13.7 GHz, and k2 of 1.8% and Q of 94 for third-order symmetric (S3) mode at 61.6 GHz. Through these results, we confirmed that even in the frequency band of approximately 60 GHz, ScAlN FBAR can achieve a Q factor approaching 100 with optimized fabrication and acoustic/EM design. Further development calls for stacks with better quality in piezoelectric and metallic layers.
摘要
Timely and Efficient Information Delivery in Real-Time Industrial IoT Networks
paper_authors: Hossam Farag, Dejan Vukobratovic, Andrea Munari, Cedomir Stefanovic
for: 支持自动化、自组织和重新配置的工业自动化，以支持第四代工业和未来的第五代工业。
methods: 使用 SIC 助手实现实时 IIoT 网络，报文根据监测现象特定的事件生成概率生成报文，并在块抖动通道上使用顺序扫描取消干扰来解码用户包。
results: 比较了 SIC 和标准频分多路复用（SDMA）的性能，发现采用 SIC 可以提高 Age of Information（AoI）、吞吐量和延迟违反概率，并且 analytical 结果与 simulate 结果匹配，证明投入 SIC 能力可以使这种简单的访问方法支持时间和效率的信息传输。Abstract
Enabling real-time communication in Industrial Internet of Things (IIoT) networks is crucial to support autonomous, self-organized and re-configurable industrial automation for Industry 4.0 and the forthcoming Industry 5.0. In this paper, we consider a SIC-assisted real-time IIoT network, in which sensor nodes generate reports according to an event-generation probability that is specific for the monitored phenomena. The reports are delivered over a block-fading channel to a common Access Point (AP) in slotted ALOHA fashion, which leverages the imbalances in the received powers among the contending users and applies successive interference cancellation (SIC) to decode user packets from the collisions. We provide an extensive analytical treatment of the setup, deriving the Age of Information (AoI), throughput and deadline violation probability, when the AP has access to both the perfect as well as the imperfect channel-state information. We show that adopting SIC improves all the performance parameters with respect to the standard slotted ALOHA, as well as to an age-dependent access method. The analytical results agree with the simulation based ones, demonstrating that investing in the SIC capability at the receiver enables this simple access method to support timely and efficient information delivery in IIoT networks.
摘要
在工业互联网Of Things（IIoT）网络中实现实时通信是支持自主、自组织和重新配置的工业自动化的关键，以支持第四代工业和未来的第五代工业。在这篇论文中，我们考虑了基于SIC的实时IIoT网络，在该网络中，感知节点根据监测现象特定的事件生成报告，并将报告传输到共享Access Point（AP）中，使用阶段性混合（ALOHA）方式进行排队发送。我们对这种设计进行了详细的分析，计算了Age of Information（AoI）、吞吐量和缺刻率，并证明采用SIC技术可以提高所有性能参数，比较于标准的阶段性混合和年龄依存的访问方法。我们的分析结果与实验结果一致，表明在接收器拥有SIC能力时，这种简单的访问方法可以支持有效和准时的信息传输在IIoT网络中。
AA-DL: AoI-Aware Deep Learning Approach for D2D-Assisted Industrial IoT
For: 本研究提出了一种基于深度学习的 Age of Information (AoI) 感知方法，以最小化在工业互联网上的峰值信息年龄 (PAoI)。* Methods: 通过 Stochastic Geometry 分析成功概率和平均 PAoI，并以优化问题的形式解决非 convex 的调度问题，开发了一种基于 Geographic Location Information (GLI) 的神经网络结构，并通过反馈Stage 进行无监督学习。* Results: 对于 randomly deployed 网络， AA-DL 方法能够提高 PAoI 性能，并与传统迭代优化方法相比，具有更低的复杂性。Abstract
In real-time Industrial Internet of Things (IIoT), e.g., monitoring and control scenarios, the freshness of data is crucial to maintain the system functionality and stability. In this paper, we propose an AoI-Aware Deep Learning (AA-DL) approach to minimize the Peak Age of Information (PAoI) in D2D-assisted IIoT networks. Particularly, we analyzed the success probability and the average PAoI via stochastic geometry, and formulate an optimization problem with the objective to find the optimal scheduling policy that minimizes PAoI. In order to solve the non-convex scheduling problem, we develop a Neural Network (NN) structure that exploits the Geographic Location Information (GLI) along with feedback stages to perform unsupervised learning over randomly deployed networks. Our motivation is based on the observation that in various transmission contexts, the wireless channel intensity is mainly influenced by distancedependant path loss, which could be calculated using the GLI of each link. The performance of the AA-DL method is evaluated via numerical results that demonstrate the effectiveness of our proposed method to improve the PAoI performance compared to a recent benchmark while maintains lower complexity against the conventional iterative optimization method.
摘要
在实时工业互联网（IIoT）应用中，例如监控和控制场景中，数据的新鲜度是维护系统功能和稳定性的关键。在这篇论文中，我们提出了一种基于AoI-Aware Deep Learning（AA-DL）的方法，以最小化在D2D协助IIoT网络中的峰值信息年龄（PAoI）。我们通过杂因统计学分析成功概率和平均PAoI，并将优化问题转化为找到最佳调度策略，以最小化PAoI。由于调度问题是非凸问题，我们开发了一种基于地理位置信息（GLI）和反馈stage的神经网络结构，以进行无监督学习。我们的动机是基于不同传输上下文中的无线通信频率强度主要受到距离参差的路径损失影响，这可以通过每个链接的GLI来计算。我们的AA-DL方法的性能通过数字结果展示，与最近的参考方法相比，可以提高PAoI性能，同时与传统迭代优化方法相比，具有较低的复杂性。
Modulation For Modulo: A Sampling-Efficient High-Dynamic Range ADC
for: This paper aims to develop an efficient high dynamic range (HDR) analog-to-digital converter (ADC) with fewer bits by using phase modulation (PM) instead of oversampling.
methods: The paper proposes using PM to modulate the phase of a carrier signal with the analog input, which allows for HDR-ADC functionality with a low-dynamic range (DR) ADC and fewer bits. The authors also derive identifiability results for reconstruction of the original signal from PM samples acquired at the Nyquist rate.
results: The authors demonstrate the efficiency of their PM-based approach with lower reconstruction errors and reduced sampling rates, and show that their hardware prototype can reconstruct signals ten times greater than the ADC’s DR from Nyquist rate samples. This has the potential to replace high-bit rate HDR-ADCs while meeting existing bit rate needs.Abstract
In high-dynamic range (HDR) analog-to-digital converters (ADCs), having many quantization bits minimizes quantization errors but results in high bit rates, limiting their application scope. A strategy combining modulo-folding with a low-DR ADC can create an efficient HDR-ADC with fewer bits. However, this typically demands oversampling, increasing the overall bit rate. An alternative method using phase modulation (PM) achieves HDR-ADC functionality by modulating the phase of a carrier signal with the analog input. This allows a low-DR ADC with fewer bits. We've derived identifiability results enabling reconstruction of the original signal from PM samples acquired at the Nyquist rate, adaptable to various signals and non-uniform sampling. Using discrete phase demodulation algorithms for practical implementation, our PM-based approach doesn't require oversampling in noise-free conditions, contrasting with modulo-based ADCs. With noise, our PM-based HDR method demonstrates efficiency with lower reconstruction errors and reduced sampling rates. Our hardware prototype illustrates reconstructing signals ten times greater than the ADC's DR from Nyquist rate samples, potentially replacing high-bit rate HDR-ADCs while meeting existing bit rate needs.
摘要
高动态范围（HDR）数字化到analog（ADC） converter中，具有多个量化比会减少量化错误，但会导致高比特率，限制其应用范围。一种将模ulo-folding与低动态范围（DR）ADC结合的策略可以创建高效的HDR-ADC，但通常需要过样 rate。另一种使用相位调制（PM）方法可以实现HDR-ADC功能，将模拟输入电压调制到干扰信号的相位中。这使得低DR ADC可以使用 fewer bits。我们已经 derive了可 identificability 结果，允许从PM样本中重建原始信号，适用于不同的信号和非均匀采样。使用离散相位解耗算法实现实用，我们的PM-based方法不需要过样 rate，与模ulo-based ADCs 不同。在噪声情况下，我们的PM-based HDR方法表现高效，具有较低的重建错误和降低的采样率。我们的硬件原型示例了从 Nyquist 速率样本中重建信号，大于 ADC 的 DR 的十倍，可能替代高比特率 HDR-ADC，同时满足现有的比特率需求。
A model-free approach to fingertip slip and disturbance detection for grasp stability inference
results: 我们使用了高敏感的USkin感觉传感器和Allegro手臂进行测试和验证，结果表明，提出的方法可以在线进行滑动检测，有效提高机器人对物体抓取稳定性。Abstract
Robotic capacities in object manipulation are incomparable to those of humans. Besides years of learning, humans rely heavily on the richness of information from physical interaction with the environment. In particular, tactile sensing is crucial in providing such rich feedback. Despite its potential contributions to robotic manipulation, tactile sensing is less exploited; mainly due to the complexity of the time series provided by tactile sensors. In this work, we propose a method for assessing grasp stability using tactile sensing. More specifically, we propose a methodology to extract task-relevant features and design efficient classifiers to detect object slippage with respect to individual fingertips. We compare two classification models: support vector machine and logistic regression. We use highly sensitive Uskin tactile sensors mounted on an Allegro hand to test and validate our method. Our results demonstrate that the proposed method is effective in slippage detection in an online fashion.
摘要
人工智能在物体抓取方面的能力与人类不可比，人类需要年月学习，并且吸取环境物理互动的充足信息。特别是感觉感知对于提供丰富反馈是关键。虽然感觉感知在机器人抓取中具有潜在的贡献，但是它在实践中得到更少的利用，主要是因为感觉传感器的时间序列复杂度。在这种情况下，我们提出了一种方法，用于评估抓取稳定性使用感觉传感。更 Specifically，我们提出了一种方法来提取任务相关特征，并设计高效的分类器来检测对各个手指的物体滑倒。我们比较了两种分类模型：支持向量机和折衣函数回归。我们使用了高敏感的优斯金感觉传感器，并 mounted on an Allegro hand来测试和验证我们的方法。我们的结果表明，我们的方法在线上可以有效地检测滑倒。
Optimal Time of Arrival Estimation for MIMO Backscatter Channels
results: 研究发现，对于通常的$M\times N$静脉拓扑，估计误差的均方误差（MSE）为$\frac{M+N-1}{MN}\sigma^2_0$；对于通常的$M\times M$坐标拓扑，其MSE为$\frac{2M-1}{M^2}\sigma^2_0$（对于对角通道）和$\frac{M-1}{M^2}\sigma^2_0$（对于不对角通道），其中$\sigma^2_0$是传统最小二乘估计器的MSE。此外，我们还 deriv了MIMO反射通道TOA估计器的Cramer-Rao下界（CRLB），表明该估计器是优化的。实验结果表明，该TOA估计器可以在大规模MIMO系统中明显提高估计和定位精度。Abstract
In this paper, we propose a novel time of arrival (TOA) estimator for multiple-input-multiple-output (MIMO) backscatter channels in closed form. The proposed estimator refines the estimation precision from the topological structure of the MIMO backscatter channels, and can considerably enhance the estimation accuracy. Particularly, we show that for the general $M \times N$ bistatic topology, the mean square error (MSE) is $\frac{M+N-1}{MN}\sigma^2_0$, and for the general $M \times M$ monostatic topology, it is $\frac{2M-1}{M^2}\sigma^2_0$ for the diagonal subchannels, and $\frac{M-1}{M^2}\sigma^2_0$ for the off-diagonal subchannels, where $\sigma^2_0$ is the MSE of the conventional least square estimator. In addition, we derive the Cramer-Rao lower bound (CRLB) for MIMO backscatter TOA estimation which indicates that the proposed estimator is optimal. Simulation results verify that the proposed TOA estimator can considerably improve both estimation and positioning accuracy, especially when the MIMO scale is large.
摘要
在这篇论文中，我们提出了一种新的时刻到达（TOA）估计器 для多输入多输出（MIMO）反射通道，其形式为关闭式。我们的估计器利用MIMO反射通道的 topological structure 进行精细的估计精度，可以显著提高估计精度。特别是，我们表明在$M \times N$ 的双Static拓扑中，MSE的平均值为 $\frac{M+N-1}{MN}\sigma^2_0$，在$M \times M$ 的单Static拓扑中，对于对角子通道，MSE的平均值为 $\frac{2M-1}{M^2}\sigma^2_0$，对于偏角子通道，MSE的平均值为 $\frac{M-1}{M^2}\sigma^2_0$，其中 $\sigma^2_0$ 是传统最小二乘估计器的MSE。此外，我们 derive了MIMO反射 TOA 估计的 Cramer-Rao lower bound (CRLB)，这表明我们的估计器是优化的。实验结果表明，我们的 TOA 估计器可以明显提高估计和定位精度，特别是当MIMO尺度较大时。
Joint Distributed Precoding and Beamforming for RIS-aided Cell-Free Massive MIMO Systems
results: 数字结果验证了提议的分布式预编码和扫描方法的有效性，并证明了它们在复杂度和扩展性方面比中央化方法更佳。Abstract
The amalgamation of cell-free networks and reconfigurable intelligent surface (RIS) has become a prospective technique for future sixth-generation wireless communication systems. In this paper, we focus on the precoding and beamforming design for a downlink RIS-aided cell-free network. The design is formulated as a non-convex optimization problem by jointly optimizing the combining vector, active precoding, and passive RIS beamforming for minimizing the weighted sum of users' mean square error. A novel joint distributed precoding and beamforming framework is proposed to decentralize the alternating optimization method for acquiring a suboptimal solution to the design problem. Finally, numerical results validate the effectiveness of the proposed distributed precoding and beamforming framework, showing its low-complexity and improved scalability compared with the centralized method.
摘要
“细胞自由网络和可重新配置智能表面（RIS）的结合技术已成为未来第六代无线通信系统的可能性。本文关注了下行RIS协助细胞自由网络的 precoding 和 beamforming 设计，设计问题由jointly 优化combining vector、活动 precoding 和 passive RIS beamforming，以最小化用户的平均方差误差。我们提出了一种分布式 precoding 和 beamforming 框架，以解决 alternating 优化法中的优化问题，并提供了一种低复杂度和高扩展性的解决方案。最后，数值结果证明了我们的提议的分布式 precoding 和 beamforming 框架的有效性，并与中央化方法相比，显示了它的低复杂度和高扩展性。”