results: 研究结果表明，当一个恶意的ND-RIS被部署时，可以使得下链路性能受到极大的降低，并且这种攻击是无动作的和难以探测的。Abstract
While reconfigurable intelligent surface (RIS) technology has been shown to provide numerous benefits to wireless systems, in the hands of an adversary such technology can also be used to disrupt communication links. This paper describes and analyzes an RIS-based attack on multi-antenna wireless systems that operate in time-division duplex mode under the assumption of channel reciprocity. In particular, we show how an RIS with a non-diagonal (ND) phase shift matrix (referred to here as an ND-RIS) can be deployed to maliciously break the channel reciprocity and hence degrade the downlink network performance. Such an attack is entirely passive and difficult to detect. We provide a theoretical analysis of the degradation in the sum ergodic rate that results when an arbitrary malicious ND-RIS is deployed and design an approach based on the genetic algorithm for optimizing the ND structure under partial knowledge of the available channel state information. Our simulation results validate the analysis and demonstrate that an ND-RIS channel reciprocity attack can dramatically reduce the downlink throughput.
摘要
“弹性智能表面（RIS）技术已经被证明可以提供无线系统中的许多优点，但在敌人手上可以使用这技术来中断通信链接。本纸描述了一种基于RIS的攻击，对于在时分多普遍调幅模式下运行的多antenna无线系统进行破坏。具体来说，我们显示了如何在ND项目（non-diagonal）的RIS中部署恶意的项目，以破坏通道对称性，从而降低下联网性能。这种攻击是完全被动的，难以检测。我们提供了一个理论分析，以及基于生物算法来优化ND结构的方法，以对不完全知道可用通道状态信息进行优化。我们的实验结果证实了分析，并显示了ND-RIS通道对称性攻击可以导致下联网通过率的严重下降。”Note: The translation is done using Google Translate and may not be perfect. Please let me know if you need further assistance.
results: 本文通过应用压缩спектrum于人体心跳间隔（RR）序列，发现健康年轻人RR序列在律 log-log 尺度上表现类似于1/f 噪声，而健康老年人RR序列则表现不同。Abstract
Signal processing and Information theory are two disparate fields used for characterizing signals for various scientific and engineering applications. Spectral/Fourier analysis, a technique employed in signal processing, helps estimation of power at different frequency components present in the signal. Characterizing a time-series based on its average amount of information (Shannon entropy) is useful for estimating its complexity and compressibility (eg., for communication applications). Information theory doesn't deal with spectral content while signal processing doesn't directly consider the information content or compressibility of the signal. In this work, we attempt to bring the fields of signal processing and information theory together by using a lossless data compression algorithm to estimate the amount of information or `compressibility' of time series at different scales. To this end, we employ the Effort-to-Compress (ETC) algorithm to obtain what we call as a Compression Spectrum. This new tool for signal analysis is demonstrated on synthetically generated periodic signals, a sinusoid, chaotic signals (weak and strong chaos) and uniform random noise. The Compression Spectrum is applied on heart interbeat intervals (RR) obtained from real-world normal young and elderly subjects. The compression spectrum of healthy young RR tachograms in the log-log scale shows behaviour similar to $1/f$ noise whereas the healthy old RR tachograms show a different behaviour. We envisage exciting possibilities and future applications of the Compression Spectrum.
摘要
信号处理和信息理论是两个不同的领域，用于描述信号的不同科学和工程应用。spectral/ fourier分析是信号处理中使用的技术，可以为不同频率组成的信号估算能量。基于时间序列的平均信息量（Shannon entropy）的Characterizing是用于估算信号的复杂性和压缩性（例如， для通信应用）。信息理论不考虑频谱内容，而信号处理不直接考虑信号的信息内容或压缩性。在这项工作中，我们尝试将信号处理和信息理论两个领域联系起来，使用一种无损数据压缩算法来估算时间序列的信息量或“压缩性”。为此，我们使用Effort-to-Compress（ETC）算法获得一个压缩спектrum。这种新的信号分析工具在人工生成的 периодические信号、sinusoid信号、混沌信号（弱和强混沌）以及随机噪声上进行了应用。压缩спектrum在实际获得的心跳间隔（RR）上进行了应用，并在径向均衡尺度上显示了类似于1/f噪声的行为。我们看到了未来应用的激动人心。
Brief Architectural Survey of Biopotential Recording Front-Ends since the 1970s
For: The paper provides a survey of the architecture history of biopotential recording front-ends developed since the 1970s, and discusses overall key circuit techniques for reliable and continuous signal acquisition.* Methods: The paper discusses various front-end architectures for biopotential recording, including their characteristics and challenges, depending on the bioelectric signals being measured.* Results: The paper provides an overview of the evolution of biopotential recording front-ends over the last five decades, and discusses the key circuit techniques for low power and low noise performance.Here are the three information points in Simplified Chinese text:* For: 这篇论文提供了1970年代以来生物电动力记录前端的建筑历史，并讨论了适用于可靠连续记录的信号获取的总体关键电路技术。* Methods: 论文讨论了不同的生物电动力记录前端架构，包括它们的特点和挑战，具体取决于测量的生物电动力信号。* Results: 论文提供了过去五十年来生物电动力记录前端的演化历史，并讨论了低功耗和低噪声性能的关键电路技术。Abstract
Measuring the bioelectric signals is one of the key functions in wearable healthcare devices and implantable medical devices. The use of wearable healthcare devices has made continuous and immediate monitoring of personal health status possible. Implantable medical devices have played an important role throughout the fields of neuroscience, brain-machine (or brain-computer) interface, and rehabilitation technology. Over the last five decades, the bioelectric signals have been observed through a variety of biopotential recording front-ends, along with advances in semiconductor technology scaling and circuit techniques. Also, for reliable and continuous signal acquisition, the front-end architectures have evolved while maintaining low power and low noise performance. In this article, the architecture history of the biopotential recording front-ends developed since the 1970s is surveyed, and overall key circuit techniques are discussed. Depending on the bioelectric signals being measured, appropriate front-end architecture needs to be chosen, and the characteristics and challenges of each architecture are also covered in this article.
摘要
测量生物电子信号是现代医疗设备和嵌入式医疗设备中的关键功能之一。使用了可穿戴式医疗设备，人们可以实时、连续地监测个人健康状况。嵌入式医疗设备在神经科学、脑机 interfaces 和rehabilitation技术等领域发挥了重要作用。过去五十年，生物电子信号已经通过多种生物潜在记录前端，利用半导体技术的发展和电路技术的进步。为确保可靠和连续的信号捕获，前端架构也在不断发展，同时保持低功耗和低噪性能。在这篇文章中，自1970年代以来发展的生物潜在记录前端架构历史被评估，同时总体讲述了关键的电路技术。根据测量的生物电子信号，需要选择合适的前端架构，文章还讲述了每种架构的特点和挑战。
Self-Sustaining Oscillator with Frequency Counter for Resonance Frequency Tracking in Micro- and Nanomechanical Sensing
results: 研究结果显示，与现有的阶段锁定循环（PLL）方法相比，提出的方法具有类似或更好的性能，同时具有更低的成本和更高的使用容易度。实验测量结果与理论预测几乎完美吻合。Abstract
Nanomechanical sensors based on detecting and tracking resonance frequency shifts are to be used in many applications. Various open- and closed-loop tracking schemes, all offering a trade-off between speed and precision, have been studied both theoretically and experimentally. In this work, we advocate the use of a frequency counter as a frequency shift monitor in conjunction with a self-sustaining oscillator (SSO) nanoelectromechanical system (NEMS) configuration. We derive a theoretical model for characterizing the speed and precision of frequency measurements with state-of-the-art frequency counters. Based on the understanding provided by this model, we introduce novel enhancements to frequency counters that result in a trade-off characteristics which is on a par with the other tracking schemes. We describe a low-cost field-programmable-gate array (FPGA) based implementation for the proposed frequency counter and use it with the SSO-NEMS device in order to study its frequency tracking performance. We compare the proposed approach with the phase-locked-loop based scheme both in theory and experimentally. Our results show that similar or better performance can be achieved at a substantially lower cost and improved ease-of-use. We obtain almost perfect correspondence between the theoretical model predictions and the experimental measurements.
摘要
几种 nanomechanical 感测器基于探测和跟踪征频Shift的应用将在未来中普遍使用。各种开放和关闭loop tracking 方案，均提供了速度和精度之间的交易，已经被理论和实验研究。在这项工作中，我们建议使用频计作为征频shift 监测器，并与自持 oscillator（SSO） nanoelectromechanical system（NEMS）配置一起使用。我们 derivated一个理论模型，用于Characterizing 频度测量的速度和精度。基于这个模型，我们提出了一些新的增强，使得频计的交易特性与其他跟踪方案相当。我们描述了一种低成本的 field-programmable-gate array（FPGA）基于实现，并用其与 SSO-NEMS 设备一起研究其频度跟踪性能。我们比较了我们的方法与阶段锁相控制（PLL） 方案， both theoretically and experimentally。我们的结果表明，可以在更低的成本和更好的使用性下达到相同或更好的性能。我们实验中的结果与理论预测几乎完美匹配。
Decision-Directed Hybrid RIS Channel Estimation with Minimal Pilot Overhead
results: 比传统静脉RIS数组系统具有更高的系统spectral efficiency，减少了频率干扰。Abstract
To reap the benefits of reconfigurable intelligent surfaces (RIS), channel state information (CSI) is generally required. However, CSI acquisition in RIS systems is challenging and often results in very large pilot overhead, especially in unstructured channel environments. Consequently, the RIS channel estimation problem has attracted a lot of interest and also been a subject of intense study in recent years. In this paper, we propose a decision-directed RIS channel estimation framework for general unstructured channel models. The employed RIS contains some hybrid elements that can simultaneously reflect and sense the incoming signal. We show that with the help of the hybrid RIS elements, it is possible to accurately recover the CSI with a pilot overhead proportional to the number of users. Therefore, the proposed framework substantially improves the system spectral efficiency compared to systems with passive RIS arrays since the pilot overhead in passive RIS systems is proportional to the number of RIS elements times the number of users. We also perform a detailed spectral efficiency analysis for both the pilot-directed and decision-directed frameworks. Our analysis takes into account both the channel estimation and data detection errors at both the RIS and the BS. Finally, we present numerous simulation results to verify the accuracy of the analysis as well as to show the benefits of the proposed decision-directed framework.
摘要
通常需要通道状态信息（CSI）来收获智能重配置表面（RIS）的优点。然而，在RIS系统中获取CSI是具有挑战性和很大的尝试量，特别是在无结构通道环境中。因此，RIS通道估计问题已经吸引了很多关注并成为了近年来的研究主题。在这篇论文中，我们提议了一种基于决策的RIS通道估计框架，适用于一般的无结构通道模型。 employ 的RIS包含了一些混合元素，这些元素可同时反射和感知进来的信号。我们表明，使用这些混合RIS元素，可以准确地重建CSI，并且尝试量与用户数成正比。因此，我们提议的框架可以substantially提高系统spectral efficiency，比pasive RIS数组系统更高。我们还进行了详细的spectral efficiency分析，包括通道估计和数据检测错误在RIS和BS之间。最后，我们提供了许多的 simulations 结果，以验证分析的准确性，以及显示提议的决策导向框架的优势。
Generalised Hyperbolic State-space Models for Inference in Dynamic Systems
results: 这个论文通过应用到一个 sintetically生成的数据集和一个实际的金融时间序列上，以示其能力。Abstract
In this work we study linear vector stochastic differential equation (SDE) models driven by the generalised hyperbolic (GH) L\'evy process for inference in continuous-time non-Gaussian filtering problems. The GH family of stochastic processes offers a flexible framework for modelling of non-Gaussian, heavy-tailed characteristics and includes the normal inverse-Gaussian, variance-gamma and Student-t processes as special cases. We present continuous-time simulation methods for the solution of vector SDE models driven by GH processes and novel inference methodologies using a variant of sequential Markov chain Monte Carlo (MCMC). As an example a particular formulation of Langevin dynamics is studied within this framework. The model is applied to both a synthetically generated data set and a real-world financial series to demonstrate its capabilities.
摘要
“在这项工作中，我们研究线性向量抽象差分方程（SDE）模型，该模型由总体化幂（GH）随机过程驱动。GH随机过程家族提供非常灵活的非高准入特性模型化框架，包括正态反射差分、差分gamma和学生t过程为特殊情况。我们提出了积累时间 simulation方法来解决vector SDE模型中的GH过程，并提出了一种基于Markov链 Monte Carlo（MCMC）的新的推断方法。作为一个示例，我们研究了一种特定的Langevin动力学形式。该模型在一个 sintetically生成的数据集和一个实际世界金融时间序列上进行了应用，以示其能力。”Note that Simplified Chinese is a romanization of Chinese, and the translation may not be perfect.
Active Inference for Sum Rate Maximization in UAV-Assisted Cognitive NOMA Networks
results: simulation结果表明，相比benchmark方案，我们提出的算法可以更好地适应时间变化的网络环境，并提高积总比特率。Abstract
Given the surge in wireless data traffic driven by the emerging Internet of Things (IoT), unmanned aerial vehicles (UAVs), cognitive radio (CR), and non-orthogonal multiple access (NOMA) have been recognized as promising techniques to overcome massive connectivity issues. As a result, there is an increasing need to intelligently improve the channel capacity of future wireless networks. Motivated by active inference from cognitive neuroscience, this paper investigates joint subchannel and power allocation for an uplink UAV-assisted cognitive NOMA network. Maximizing the sum rate is often a highly challenging optimization problem due to dynamic network conditions and power constraints. To address this challenge, we propose an active inference-based algorithm. We transform the sum rate maximization problem into abnormality minimization by utilizing a generalized state-space model to characterize the time-changing network environment. The problem is then solved using an Active Generalized Dynamic Bayesian Network (Active-GDBN). The proposed framework consists of an offline perception stage, in which a UAV employs a hierarchical GDBN structure to learn an optimal generative model of discrete subchannels and continuous power allocation. In the online active inference stage, the UAV dynamically selects discrete subchannels and continuous power to maximize the sum rate of secondary users. By leveraging the errors in each episode, the UAV can adapt its resource allocation policies and belief updating to improve its performance over time. Simulation results demonstrate the effectiveness of our proposed algorithm in terms of cumulative sum rate compared to benchmark schemes.
摘要
随着无线数据交换量的增加，启发于互联网宇宙（IoT）、无人机（UAV）、认知电波（CR）和非对称多接入（NOMA）等技术的应用，Future无线网络的通道容量需要更加智能地提高。为了解决这一挑战，这篇论文提出了一种基于活动推理的 JOINT 子频率和功率分配算法。通过将总Bit rate最大化问题转化为异常值最小化问题，我们利用一种通用状态空间模型来描述时间变化的网络环境。然后，我们使用一个活动总体动态 bayesian 网络（Active-GDBN）解决这个问题。我们的框架包括在线上active inference阶段，在这个阶段，UAV使用一个层次结构的 GDBN 结构来学习精确的生成模型，以便在精确的子频率和连续的功率分配方面进行最佳化。在线上激活推理阶段，UAV会在精确的子频率和连续的功率分配方面进行动态选择，以最大化次级用户的总Bit rate。通过利用每个回合中的错误，UAV可以适应其资源分配策略和信息更新，从而提高其性能。实验结果表明，我们提出的算法在总Bit rate方面与参考方案相比表现更好。
Beamforming Design for RIS-Aided THz Wideband Communication Systems
results: simulations表明，提出的架构能够有效地减少笼形拥填的影响，提高系统的性能。Abstract
Benefiting from tens of GHz of bandwidth, terahertz (THz) communications has become a promising technology for future 6G networks. However, the conventional hybrid beamforming architecture based on frequency-independent phase-shifters is not able to cope with the beam split effect (BSE) in THz massive multiple-input multiple-output (MIMO) systems. Despite some work introducing the frequency-dependent phase shifts via the time delay network to mitigate the beam splitting in THz wideband communications, the corresponding issue in reconfigurable intelligent surface (RIS)-aided communications has not been well investigated. In this paper, the BSE in THz massive MIMO is quantified by analyzing the array gain loss. A new beamforming architecture has been proposed to mitigate this effect under RIS-aided communications scenarios. Simulations are performed to evaluate the effectiveness of the proposed system architecture in combating the array gain loss.
摘要
使用十几GHz的带宽，teraHz（THz）通信已成为未来6G网络的促进技术。然而，传统的混合 beamforming架构基于频率独立的相位调节器无法应对THz大规模多输入多输出（MIMO）系统中的束分裂效应（BSE）。虽有一些工作介绍了频率相关的相位偏移通过时延网络来mitigate THz广泛通信中的束分裂，但相关的RIS（可编程智能面）协助通信场景的研究尚未得到了充分的探讨。本文对THz大规模MIMO系统中的BSE进行了分析，并提出了一种新的束分裂 Mitigation architecture。通过实验评估了提议系统架构的效果。
Sum-Rate Maximization for Movable Antenna Enabled Multiuser Communications
results: 提高下链吞吐量和性能比FPAs更高Here’s a more detailed explanation of each point:
for: The paper is written to propose a novel multiuser communication system with movable antennas (MAs) that can enhance the downlink sum-rate by exploiting the antenna position optimization.
methods: The paper uses a joint optimization of the transmit beamforming vector and transmit MA positions to solve the non-convex problem. The authors propose an efficient algorithm that combines fractional programming, alternating optimization, and gradient descent methods to tackle the problem. As an alternative, a zero-forcing beamforming-based design is also proposed to strike a better performance-complexity trade-off.
results: Numerical investigations show that the proposed algorithms achieve better performance compared with the benchmark relying on conventional fixed-position antennas (FPAs). The proposed system can improve the downlink sum-rate and provide better performance than FPAs.Abstract
A novel multiuser communication system with movable antennas (MAs) is proposed, where the antenna position optimization is exploited to enhance the downlink sum-rate. The joint optimization of the transmit beamforming vector and transmit MA positions is studied for a multiuser multiple-input single-input system. An efficient algorithm is proposed to tackle the formulated non-convex problem via capitalizing on fractional programming, alternating optimization, and gradient descent methods. To strike a better performance-complexity trade-off, a zero-forcing beamforming-based design is also proposed as an alternative. Numerical investigations are presented to verify the efficiency of the proposed algorithms and their superior performance compared with the benchmark relying on conventional fixed-position antennas (FPAs).
摘要
新的多用户通信系统，使用可移动天线（MA），提出了一种新的天线位置优化技术，以增加下链数据率。在多用户多输入单输出系统中，joint优化传输扩散矩阵和天线位置的算法被研究。通过使用分数编程、 alternate优化和梯度下降方法，提出了一种高效的算法。为了更好地平衡性能和复杂度之间的贸易，也提出了一种基于零干扰扩散矩阵的设计。 numerically investigate the proposed algorithms and their superior performance compared with the benchmark relying on conventional fixed-position antennas (FPAs).Here is the word-for-word translation of the text into Simplified Chinese:新的多用户通信系统，使用可移动天线（MA），提出了一种新的天线位置优化技术，以增加下链数据率。在多用户多输入单输出系统中，joint优化传输扩散矩阵和天线位置的算法被研究。通过使用分数编程、 alternate优化和梯度下降方法，提出了一种高效的算法。为了更好地平衡性能和复杂度之间的贸易，也提出了一种基于零干扰扩散矩阵的设计。 numerically investigate the proposed algorithms and their superior performance compared with the benchmark relying on conventional fixed-position antennas (FPAs).
Evaluating Mental Stress Among College Students Using Heart Rate and Hand Acceleration Data Collected from Wearable Sensors
paper_authors: Moein Razavi, Anthony McDonald, Ranjana Mehta, Farzan Sasangohar for: This paper aims to develop a machine learning-based method for identifying stress using physiological data collected from college students.methods: The study uses wearable wrist-worn sensors and a mobile health application to collect heart rate and hand acceleration data, and self-reported stress data from college students. The XGBoost method was used to evaluate the effectiveness of the machine learning algorithms for stress detection.results: The study found that the XGBoost method was the most reliable model for identifying stress episodes, with an AUC of 0.64 and an accuracy of 84.5%. The standard deviation of hand acceleration, standard deviation of heart rate, and the minimum heart rate were the most important features for stress detection.Abstract
Stress is various mental health disorders including depression and anxiety among college students. Early stress diagnosis and intervention may lower the risk of developing mental illnesses. We examined a machine learning-based method for identification of stress using data collected in a naturalistic study utilizing self-reported stress as ground truth as well as physiological data such as heart rate and hand acceleration. The study involved 54 college students from a large campus who used wearable wrist-worn sensors and a mobile health (mHealth) application continuously for 40 days. The app gathered physiological data including heart rate and hand acceleration at one hertz frequency. The application also enabled users to self-report stress by tapping on the watch face, resulting in a time-stamped record of the self-reported stress. We created, evaluated, and analyzed machine learning algorithms for identifying stress episodes among college students using heart rate and accelerometer data. The XGBoost method was the most reliable model with an AUC of 0.64 and an accuracy of 84.5%. The standard deviation of hand acceleration, standard deviation of heart rate, and the minimum heart rate were the most important features for stress detection. This evidence may support the efficacy of identifying patterns in physiological reaction to stress using smartwatch sensors and may inform the design of future tools for real-time detection of stress.
摘要
stress是多种大学生心理健康问题，包括抑郁和焦虑。早期识别和 intervención可能降低创建心理疾病的风险。我们使用机器学习算法来识别心理压力，使用自报告压力作为真实参照数据，以及Physiological数据，如心 rate和手势加速度。这项研究从大学校园中采集了54名学生，他们使用腕表仪和移动医疗应用程序，连续40天收集数据。应用程序记录了每分钟一次的心 rate和手势加速度数据，同时也让用户通过触摸腕表来报告压力，从而获得了时间戳的自报告压力记录。我们创建、评估和分析了机器学习算法，用于在大学生中识别压力发作。XGBoost方法是最可靠的模型，AUC为0.64，准确率为84.5%。手势加速度的标准差、心 rate的标准差和最低心 rate是最重要的压力检测特征。这些证据可能支持通过智能手表感知器检测压力的Pattern，并且可能导向未来的实时压力检测工具的设计。
Pointing-and-Acquisition for Optical Wireless in 6G: From Algorithms to Performance Evaluation
results: 通过大量的 simulations，论文表明，提议的方法可以提供更好的链接和维护性能。Abstract
The increasing demand for wireless communication services has led to the development of non-terrestrial networks, which enables various air and space applications. Free-space optical (FSO) communication is considered one of the essential technologies capable of connecting terrestrial and non-terrestrial layers. In this article, we analyze considerations and challenges for FSO communications between gateways and aircraft from a pointing-and-acquisition perspective. Based on the analysis, we first develop a baseline method that utilizes conventional devices and mechanisms. Furthermore, we propose an algorithm that combines angle of arrival (AoA) estimation through supplementary radio frequency (RF) links and beam tracking using retroreflectors. Through extensive simulations, we demonstrate that the proposed method offers superior performance in terms of link acquisition and maintenance.
摘要
随着无线通信服务的增加需求，非地球网络的发展已经推动了各种空天应用。自由空间光学（FSO）通信被认为是连接地球和非地球层的重要技术之一。在本文中，我们分析了FSO通信 между网关和飞机从指向和捕获角度来考虑的考虑因素。根据分析结果，我们首先开发了使用普通设备和机制的基线方法。此外，我们提议一种方法，该方法利用补充Radio频信号的角度估计和反射器 beam Tracking。通过广泛的 simulations，我们证明了我们提议的方法可以提供更高的链接和维持链接性能。