results: 这篇论文提出了一种不需要干扰功率或渠道状态信息（CSI）的恶意干扰器，并提出了一种基于统计的反干扰策略。此外，论文还介绍了一种能够在存在恶意干扰的情况下估计统计CSI的数据帧结构。Abstract
Emerging intelligent reflective surfaces (IRSs) significantly improve system performance, but also pose a signifcant risk for physical layer security (PLS). Unlike the extensive research on legitimate IRS-enhanced communications, in this article we present an adversarial IRS-based fully-passive jammer (FPJ). We describe typical application scenarios for Disco IRS (DIRS)-based FPJ, where an illegitimate IRS with random, time-varying reflection properties acts like a "disco ball" to randomly change the propagation environment. We introduce the principles of DIRS-based FPJ and overview existing investigations of the technology, including a design example employing one-bit phase shifters. The DIRS-based FPJ can be implemented without either jamming power or channel state information (CSI) for the legitimate users (LUs). It does not suffer from the energy constraints of traditional active jammers, nor does it require any knowledge of the LU channels. In addition to the proposed jamming attack, we also propose an anti-jamming strategy that requires only statistical rather than instantaneous CSI. Furthermore, we present a data frame structure that enables the legitimate access point (AP) to estimate the statistical CSI in the presence of the DIRS jamming. Typical cases are discussed to show the impact of the DIRS-based FPJ and the feasibility of the anti-jamming precoder. Moreover, we outline future research directions and challenges for the DIRS-based FPJ and its anti-jamming precoding to stimulate this line of research and pave the way for practical applications.
摘要
emerging intelligent reflective surfaces (IRSs) significantly improve system performance, but also pose a significant risk for physical layer security (PLS). unlike the extensive research on legitimate IRS-enhanced communications, in this article we present an adversarial IRS-based fully-passive jammer (FPJ). we describe typical application scenarios for Disco IRS (DIRS)-based FPJ, where an illegitimate IRS with random, time-varying reflection properties acts like a "disco ball" to randomly change the propagation environment. we introduce the principles of DIRS-based FPJ and overview existing investigations of the technology, including a design example employing one-bit phase shifters. the DIRS-based FPJ can be implemented without either jamming power or channel state information (CSI) for the legitimate users (LUs). it does not suffer from the energy constraints of traditional active jammers, nor does it require any knowledge of the LU channels. in addition to the proposed jamming attack, we also propose an anti-jamming strategy that requires only statistical rather than instantaneous CSI. furthermore, we present a data frame structure that enables the legitimate access point (AP) to estimate the statistical CSI in the presence of the DIRS jamming. typical cases are discussed to show the impact of the DIRS-based FPJ and the feasibility of the anti-jamming precoder. moreover, we outline future research directions and challenges for the DIRS-based FPJ and its anti-jamming precoding to stimulate this line of research and pave the way for practical applications.
Sequential Monte Carlo Graph Convolutional Network for Dynamic Brain Connectivity
methods: 该方法基于粒子滤波算法，可以在只有部分和噪声的观察数据情况下，不假设站立性的连接topology，并通过Sequential Monte Carlo Graph Convolutional Network (SMC-GCN)来限制干扰连接。
results: 实验研究表明，SMC-GCN方法在脑疾病分类任务中表现出色，超过了其他方法的性能。Abstract
An increasingly important brain function analysis modality is functional connectivity analysis which regards connections as statistical codependency between the signals of different brain regions. Graph-based analysis of brain connectivity provides a new way of exploring the association between brain functional deficits and the structural disruption related to brain disorders, but the current implementations have limited capability due to the assumptions of noise-free data and stationary graph topology. We propose a new methodology based on the particle filtering algorithm, with proven success in tracking problems, which estimates the hidden states of a dynamic graph with only partial and noisy observations, without the assumptions of stationarity on connectivity. We enrich the particle filtering state equation with a graph Neural Network called Sequential Monte Carlo Graph Convolutional Network (SMC-GCN), which due to the nonlinear regression capability, can limit spurious connections in the graph. Experiment studies demonstrate that SMC-GCN achieves the superior performance of several methods in brain disorder classification.
摘要
▼ 请注意，以下文本将被翻译成简化中文。一种日益重要的大脑功能分析方法是函数连接分析，它视连接为脑区域信号的统计 codependency。基于图的Brain Connectivity分析提供了一种探索脑功能缺陷和脑疾病相关的结构性破坏的新方法，但现有实现受限因为假设了噪声自由数据和静止的图表结构。我们提出了一种基于粒子滤波算法的新方法，该算法在跟踪问题中证明了成功，可以在只有部分和噪声的观察数据情况下估计图中隐藏的状态。我们在粒子滤波状态方程中添加了一种图神经网络 called Sequential Monte Carlo Graph Convolutional Network (SMC-GCN)，该网络具有非线性回归能力，可以限制图中的假设连接。实验研究表明，SMC-GCN可以在脑疾病分类方面达到更高的性能。
Nonlinear Multi-Carrier System with Signal Clipping: Measurement, Analysis, and Optimization
for: Reducing the peak-to-average power ratio (PAPR) in OFDM systems
methods: Using the Bessel-Fourier PA (BFPA) model to analyze the nonlinearity of the power amplifier (PA), and simplifying the power expression using inter-modulation product (IMP) analysis
results: Optimizing the system setting for a nonlinear clipped OFDM system to achieve the symbol error rate (SER) lower bound in a practical system that considers both PA nonlinearity and clipping distortion.Abstract
Signal clipping is a classic technique for reducing peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. It has been widely applied in consumer electronic devices owing to its low complexity and high efficiency. Although clipping reduces the nonlinear distortion caused by power amplifiers (PAs), it induces additional clipping distortion. Optimizing the joint system performance with consideration of both PA nonlinearity and clipping distortion remains an open problem due to the complex PA modeling. In this paper, we analyze the PA nonlinearity through the Bessel-Fourier PA (BFPA) model and simplify its power expression using inter-modulation product (IMP) analysis. We derive expressions of the receiver signal-to-noise ratio (SNR) and system symbol error rate (SER) for the nonlinear clipped OFDM system. With the derivations, we investigate the optimal system setting to achieve the SER lower bound in a practical OFDM system that considers both PA nonlinearity and clipping distortion. The methods and results presented in this paper can serve as a useful reference for the system-level optimization of clipped OFDM systems with nonlinear PA.
摘要
<>TRANSLATE_TEXTSignal clipping is a classic technique for reducing peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. It has been widely applied in consumer electronic devices owing to its low complexity and high efficiency. Although clipping reduces the nonlinear distortion caused by power amplifiers (PAs), it induces additional clipping distortion. Optimizing the joint system performance with consideration of both PA nonlinearity and clipping distortion remains an open problem due to the complex PA modeling. In this paper, we analyze the PA nonlinearity through the Bessel-Fourier PA (BFPA) model and simplify its power expression using inter-modulation product (IMP) analysis. We derive expressions of the receiver signal-to-noise ratio (SNR) and system symbol error rate (SER) for the nonlinear clipped OFDM system. With the derivations, we investigate the optimal system setting to achieve the SER lower bound in a practical OFDM system that considers both PA nonlinearity and clipping distortion. The methods and results presented in this paper can serve as a useful reference for the system-level optimization of clipped OFDM systems with nonlinear PA.TRANSLATE_TEXT
An IRS-Assisted Secure Dual-Function Radar-Communication System
methods: 使用智能反射 superficie（IRS）和人工噪声（AN），并optimize the radar waveform, AN jamming noise, and IRS parameters to maximize the communication secrecy rate while meeting radar signal-to-noise ratio（SNR） constraints.
results: 提出一种新的系统设计方案，并使用分数编程技术将分数形目标函数转化为更易处理的非分数多项式。数值结果表明系统设计算法的收敛性，并显示了噪声分配对系统安全性的影响。Abstract
In dual-function radar-communication (DFRC) systems the probing signal contains information intended for the communication users, which makes that information vulnerable to eavesdropping by the targets. We propose a novel design for enhancing the physical layer security (PLS) of DFRC systems, via the help of intelligent reflecting surface (IRS) and artificial noise (AN), transmitted along with the probing waveform. The radar waveform, the AN jamming noise and the IRS parameters are designed to optimize the communication secrecy rate while meeting radar signal-to-noise ratio (SNR) constrains. Key challenges in the resulting optimization problem include the fractional form objective, the SNR being a quartic function of the IRS parameters, and the unit-modulus constraint of the IRS parameters. A fractional programming technique is used to transform the fractional form objective of the optimization problem into more tractable non-fractional polynomials. Numerical results are provided to demonstrate the convergence of the proposed system design algorithm, and also show the impact of the power assigned to the AN on the secrecy performance of the designed system.
摘要
在双功能雷达通信（DFRC）系统中，探测信号包含向通信用户传递的信息，因此这些信息容易受到目标的窃听。我们提议一种新的设计方案，以增强双功能雷达通信系统的物理层安全性（PLS），通过利用智能反射表面（IRS）和人工噪声（AN），同探测波形一起传输。雷达波形、噪声干扰和IRS参数是根据优化通信秘密率的要求，同时满足雷达信号响应比（SNR）的限制。关键挑战包括分数形目标函数、SNR为IRS参数的四次函数，以及IRS参数的单位模式约束。我们使用分数编程技术将分数形目标函数转换为更易处理的非分数多项式。numerical results show that the proposed system design algorithm converges and demonstrate the impact of the power assigned to the AN on the secrecy performance of the designed system.Note: Please note that the translation is in Simplified Chinese, which is one of the two standard forms of Chinese writing. If you prefer Traditional Chinese, please let me know and I will be happy to provide the translation in that form instead.
An Experimental Prototype for Multistatic Asynchronous ISAC
results: 实验结果表明，多Static ISAC系统可以提供更高的感知能力，具有多视角的接收节点空间多样性。Abstract
We prototype and validate a multistatic mmWave ISAC system based on IEEE802.11ay. Compensation of the clock asynchrony between each TX and RX pair is performed using the sole LoS wireless signal propagation. As a result, our system provides concurrent target tracking and micro-Doppler estimation from multiple points of view, paving the way for practical multistatic data fusion. Our results on human movement sensing, complemented with precise, quantitative GT data, demonstrate the enhanced sensing capabilities of multistatic ISAC, due to the spatial diversity of the receiver nodes.
摘要
我们研究和验证了一个基于IEEE802.11ay的多态 millimeter wave ISAC系统。我们使用唯一的视线无线信号媒体进行时钟偏差补偿，因此我们的系统可以同时进行目标跟踪和微多普勒估算，从多个视点来源获得实用的数据融合。我们对人体运动感知进行了补充，并且通过精确的量化GT数据，示出了多态 ISAC的感知能力的增强，即因为接收节点的空间多样性。