results: 比BPA更高效，但图像质量与BPA相当，计算时间减少90%。Abstract
Rotating Synthetic Aperture Radar (ROSAR) can generate a 360$^\circ$ image of its surrounding environment using the collected data from a single moving track. Due to its non-linear track, the Back-Projection Algorithm (BPA) is commonly used to generate SAR images in ROSAR. Despite its superior imaging performance, BPA suffers from high computation complexity, restricting its application in real-time systems. In this paper, we propose an efficient imaging method based on robust sparse array synthesis. It first conducts range-dimension matched filtering, followed by azimuth-dimension matched filtering using a selected sparse aperture and filtering weights. The aperture and weights are computed offline in advance to ensure robustness to array manifold errors induced by the imperfect radar rotation. We introduce robust constraints on the main-lobe and sidelobe levels of filter design. The resultant robust sparse array synthesis problem is a non-convex optimization problem with quadratic constraints. An algorithm based on feasible point pursuit and successive convex approximation is devised to solve the optimization problem. Extensive simulation study and experimental evaluations using a real-world hardware platform demonstrate that the proposed algorithm can achieve image quality comparable to that of BPA, but with a substantial reduction in computational time up to 90%.
摘要
绕转synthetic aperture radar（ROSAR）可以使用收集的数据生成360度的环境图像，而不需要多个静止轨迹。由于其非线性轨迹，因此通常使用回投算法（BPA）生成SAR图像。尽管它的图像性能更高，但BPA受到高计算复杂性的限制，因此无法应用于实时系统。在这篇论文中，我们提出了一种高效的图像方法，基于强健的稀疏阵列synthesis。它首先进行距离维度匹配滤波，然后使用选择的稀疏阵列和滤波加重来进行 azimuth维度匹配滤波。阵列和加重在线上预计算，以确保对雷达旋转induced的阵列 manifold errors 的Robustness。我们引入了主ibeam和副ibeam水平的Robust constraints。结果的强健稀疏阵列synthesis问题是非束convEX optimization问题，其中 quadratic constraints。我们提出了基于可行点追求和successive convex approximation的算法来解决优化问题。广泛的模拟研究和使用实际硬件平台进行的实验评估表明，提议的算法可以实现与BPA相同的图像质量，但计算时间减少了90%。
On Distributed and Asynchronous Sampling of Gaussian Processes for Sequential Binary Hypothesis Testing
results: 研究者们发现了采样时间对顺序测试的影响，并提供了采样时间的下界和上界。他们还通过数值计算来证明了理论结论的正确性。Abstract
In this work, we consider a binary sequential hypothesis testing problem with distributed and asynchronous measurements. The aim is to analyze the effect of sampling times of jointly \textit{wide-sense stationary} (WSS) Gaussian observation processes at distributed sensors on the expected stopping time of the sequential test at the fusion center (FC). The distributed system is such that the sensors and the FC sample observations periodically, where the sampling times are not necessarily synchronous, i.e., the sampling times at different sensors and the FC may be different from each other. \color{black} The sampling times, however, are restricted to be within a time window and a sample obtained within the window is assumed to be \textit{uncorrelated} with samples outside the window. We also assume that correlations may exist only between the observations sampled at the FC and those at the sensors in a pairwise manner (sensor pairs not including the FC have independent observations). The effect of \textit{asynchronous} sampling on the SPRT performance is analyzed by obtaining bounds for the expected stopping time. We illustrate the validity of the theoretical results with numerical results.
摘要
在这项工作中，我们考虑了一个二进制顺序假设测试问题，其中测量过程是分布式和 asynchronous。我们想要分析在分布式感知器和汇中心（FC）之间的共同 Gaussian 观测过程中，采样时间的影响。我们假设了所有感知器和FC在Periodically采样观测数据，但采样时间不一定同步。具体来说，采样时间在不同的感知器和FC之间可能不同。然而，采样时间都限制在一个时间窗口内，而在这个窗口内采样的样本假设是独立的。我们还假设了感知器对感知器之间的观测是对称的，即感知器对感知器之间的观测是独立的。我们分析了异步采样对 SPRT 性能的影响，并获得了预期停止时间的下界。我们通过数据示例来证明理论结果的正确性。
Kullback-Leibler Divergence-Guided Copula Statistics-Based Blind Source Separation of Dependent Signals
results: 实验结果表明，基于 copula 统计的盲源分离方法在11-Bus 4-Machine 系统中的时域分析数据上 converges faster 并且表现更好，相比之下 state-of-the-art 盲源分离方法。Abstract
In this paper, we propose a blind source separation of a linear mixture of dependent sources based on copula statistics that measure the non-linear dependence between source component signals structured as copula density functions. The source signals are assumed to be stationary. The method minimizes the Kullback-Leibler divergence between the copula density functions of the estimated sources and of the dependency structure. The proposed method is applied to data obtained from the time-domain analysis of the classical 11-Bus 4-Machine system. Extensive simulation results demonstrate that the proposed method based on copula statistics converges faster and outperforms the state-of-the-art blind source separation method for dependent sources in terms of interference-to-signal ratio.
摘要
在这篇论文中，我们提出了一种基于 copula 统计的无参源分离方法，用于分解线性混合的相关源信号。我们假设源信号是站ARY的。方法的目标是将 copula density function 的两个分布匹配，以最小化库拉-莱布勒散度的差异。我们对来自经典 11-Bus 4-Machine 系统的时域分析数据进行了应用。广泛的 simulate 结果表明，基于 copula 统计的方法在相关源信号分离方面比现有的方法更快 converge 和有更高的干扰比信号比。
Enhancing Performance, Calibration Time and Efficiency in Brain-Machine Interfaces through Transfer Learning and Wearable EEG Technology
results: 研究获得了多Session的 motor-movement EEG 数据，并在 TL 下实现了96% 的 inter-session 精度，大大减少了准确时间和使用度。透过在 Edge 上执行推断 every 100ms，系统估计可以实现30小时的电池生命。Abstract
Brain-machine interfaces (BMIs) have emerged as a transformative force in assistive technologies, empowering individuals with motor impairments by enabling device control and facilitating functional recovery. However, the persistent challenge of inter-session variability poses a significant hurdle, requiring time-consuming calibration at every new use. Compounding this issue, the low comfort level of current devices further restricts their usage. To address these challenges, we propose a comprehensive solution that combines a tiny CNN-based Transfer Learning (TL) approach with a comfortable, wearable EEG headband. The novel wearable EEG device features soft dry electrodes placed on the headband and is capable of on-board processing. We acquire multiple sessions of motor-movement EEG data and achieve up to 96% inter-session accuracy using TL, greatly reducing the calibration time and improving usability. By executing the inference on the edge every 100ms, the system is estimated to achieve 30h of battery life. The comfortable BMI setup with tiny CNN and TL paves the way to future on-device continual learning, essential for tackling inter-session variability and improving usability.
摘要
Brain-machine interfaces (BMIs) 蜕化为助手技术的新动力，激活人们的 motor 功能障碍，并且使得设备控制和功能恢复更加容易。然而，在每次使用时需要时间consuming的 calibration 仍然是一大障碍。此外，现有的设备舒适度还是一个限制因素。为了解决这些挑战，我们提出了一个综合解决方案，结合 tiny CNN 基于传输学习 (TL) 的方法，以及舒适可穿戴的 EEG 头盔。这种新的 EEG 设备采用软干电极置于头盔上，并可以在设备上进行处理。我们收集了多个 motor 运动 EEG 数据，并使用 TL 实现了96%的session accuracy，从而大幅减少了 calibration 时间，并提高了使用性。通过在边缘进行每100ms的执行推理，系统估计可以达到30小时的电池寿命。舒适的 BMI 设置，结合 tiny CNN 和 TL，为未来的在设备上进行不断学习做出了重要贡献，以解决inter-session variability和提高使用性。
Stochastic Phased Array Performance Indicators for Quality-of-Service-Enhanced Massive MIMO
results: 研究结果表明，高IEG和低BCC的天线排布可以提高融合总bitrate和减少调度需求。Abstract
In this paper, we show that the signal-to-interference-plus-noise ratio (SINR) at a base station (BS) equipped with an arbitrary physical array antenna can be expressed as a function of two fundamental figures-of-merit (FoMs): (I) the instantaneous effective gain (IEG), and (II) the beamforming-channel correlation (BCC). These two FoMs are functions of the array antenna layout, the antenna elements, the propagation channel and the applied signal processing algorithms, and hence they are random variables (RVs) in general. We illustrate that both FoMs provide essential insights for quality-of-service (QoS)-based phased array design by investigating their statistics for BSs applying full-digital (FD) zero forcing (ZF) beamforming. We evaluate various array designs and show that arrays with higher IEGs and a reduced probability of low BCCs can increase the ergodic sum rate and reduce the need for scheduling.
摘要
在这篇论文中，我们显示了基站（BS）装备任意物理数组天线的信号吞吐量较干扰噪声比（SINR）可以表示为两个基本的优势因素（FoM）：（I）即时效果的辐射增益（IEG），和（II）扫描通道卷积（BCC）。这两个 FoM 是天线阵列布局、天线元件、传播通道和应用的信号处理算法的函数，因此它们是随机变量（RV）的一般情况。我们表明了这两个 FoM 对服务质量（QoS）基于天线阵列设计带来了重要的洞察，通过研究这两个 FoM 的统计特性来评估不同的天线阵列设计。我们评估了多种阵列设计，并显示了高IEG和低BCC的概率可以提高杂合辐射率和减少调度需求。
Performance Analysis of RIS/STAR-IOS-aided V2V NOMA/OMA Communications over Composite Fading Channels
paper_authors: Farshad Rostami Ghadi, Masoud Kaveh, Diego Martin
For: 本研究探讨了基于协助器（RIS）和同时发射和反射智能多面（STAR-IOS）的车辆到车辆（V2V）通信的性能，尤其是在非对称多Access（NOMA）和对称多Access（OMA）方案下。* Methods: 本研究使用了中心限定定理（CLT）来 deriv 同aje channel的PDF和CDF，并使用了Jensen不等式来提出一个Upper bound of 平均容量（EC），以及一个分析表达式来计算智能交通系统（ITS）中的能量效率（EE）。* Results: 研究结果显示，在V2V通信中应用RIS/STAR-RIS可以显著改善智能交通系统的性能，并且在NOMA和OMA场景下，considering NOMA scheme可以提供更好的性能，包括出入口概率（OP）、平均容量（EC）和能量效率（EE）。Abstract
This paper investigates the performance of vehicleto-vehicle (V2V) communications assisted by a reconfigurable intelligent surface (RIS) and a simultaneous transmitting and reflecting intelligent omni-surface (STAR-IOS) under nonorthogonal multiple access (NOMA) and orthogonal multiple access (OMA) schemes. In particular, we consider that the RIS is close to the transmitter vehicle while the STAR-IOS is near the receiver vehicles. In addition, we assume that the STAR-IOS exploits the energy-splitting (ES) protocol for communication and the fading channels between the RIS and STAR-IOS follow composite Fisher-Snedecor F distribution. Under such assumptions, we first use the central limit theorem (CLT) to derive the PDF and the CDF of equivalent channels at receiver vehicles, and then, we derive the closed-form expression of outage probability (OP) under NOMA/OMA scenarios. Additionally, by exploiting Jensen's inequality, we propose an upper bound of the ergodic capacity (EC), and then, we derive an analytical expression of the energy efficiency (EE) for both NOMA and OMA cases. Further, our analytical results, which are double-checked with the Monte-Carlo simulation, reveal that applying RIS/STAR-RIS in V2V communications can significantly improve the performance of intelligent transportation systems (ITS). Besides, the results indicate that considering the NOMA scheme provides better performance in terms of the OP, EC, and EE as compared with the OMA case for the considered V2V communication.
摘要
Using the central limit theorem (CLT), we first derive the probability distribution function (PDF) and the cumulative distribution function (CDF) of the equivalent channels at the receiver vehicles. Then, we derive a closed-form expression for the outage probability (OP) under both NOMA and OMA scenarios. Additionally, by exploiting Jensen's inequality, we propose an upper bound on the ergodic capacity (EC) and derive an analytical expression for the energy efficiency (EE) for both NOMA and OMA cases.Our analytical results, which are verified through Monte-Carlo simulations, show that incorporating RIS/STAR-IOS in V2V communications can significantly improve the performance of intelligent transportation systems (ITS). Furthermore, our results indicate that the NOMA scheme outperforms the OMA case in terms of OP, EC, and EE for the considered V2V communication.Here is the Simplified Chinese translation of the text:这篇论文研究了使用拓展智能表面（RIS）和同时传输和反射智能全面（STAR-IOS）帮助汽车间通信，以及在不对称多接入（NOMA）和对称多接入（OMA）方案下的性能。特别是，我们假设RIS靠近发送器汽车，而STAR-IOS靠近接收器汽车。此外，我们假设STAR-IOS使用能量分配（ES）协议进行通信，并且在RIS和STAR-IOS之间的投射通道遵循复合拜让-斯内多辛（F）分布。使用中心限定定律（CLT），我们首先计算发送器汽车的等效通道PDF和CDF，然后计算OP的关键值。此外，我们通过贝叶斯不等式提出OP的上限，并计算NOMA和OMA情况下的吞吐量率（EC）和能效率（EE）的分析表达式。我们的分析结果，通过对 Monte-Carlo 仿真进行验证，表明在汽车间通信中应用 RIS/STAR-IOS 可以显著提高智能交通系统（ITS）的性能。此外，我们的结果还表明，在考虑 NOMA 方案时，OP、EC 和 EE 的性能都比 OMA 情况更好。
RIS-Assisted Physical Layer Authentication for 6G Endogenous Security
results: 通过分析Received Signal Strength（RSS）基于的骗取检测方法，验证了提议的架构的可行性。实验结果显示，在不同发送源位置和同一个发送源位置下，具有3.5%和76%的性能提升。Abstract
The physical layer authentication (PLA) is a promising technology which can enhance the access security of a massive number of devices in the near future. In this paper, we propose a reconfigurable intelligent surface (RIS)-assisted PLA system, in which the legitimate transmitter can customize the channel fingerprints during PLA by controlling the ON-OFF state of the RIS. Without loss of generality, we use the received signal strength (RSS) based spoofing detection approach to analyze the feasibility of the proposed architecture. Specifically, based on the RSS, we derive the statistical properties of PLA and give some interesting insights, which showcase that the RIS-assisted PLA is theoretically feasible. Then, we derive the optimal detection threshold to maximize the performance in the context of the presented performance metrics. Next, the actual feasibility of the proposed system is verified via proof-of-concept experiments on a RIS-assisted PLA prototype platform. The experiment results show that there are 3.5% and 76% performance improvements when the transmission sources are at different locations and at the same location, respectively.
摘要
物理层身份验证（PLA）是一种有前途的技术，可以增强未来大量设备的访问安全性。在这篇论文中，我们提议了基于智能表面（RIS）的PLA系统，其中有效发送器可以在PLA中自定义通道指纹。不失一般性，我们使用基于受信号强度（RSS）的伪造探测方法来分析提议的体系的可行性。特别是基于RSS，我们 derivates了PLA的统计性质并提供了一些有趣的发现，这些发现表明RIS协助的PLA是理论上可行的。然后，我们计算了最佳检测阈值以最大化性能在所提出的性能指标下。接下来，我们验证了提议的系统的实际可行性通过一个基于RIS协助PLA的原型平台的证明实验。实验结果显示，在不同位置的发送源情况下，提议的系统具有3.5%和76%的性能提升。
Semantic reconstruction of continuous language from MEG signals
methods: 该研究使用了一种数据驱动的方法，首先使用对比学习训练多个参与者的决定模型，然后使用搜索算法生成基于 MEG 数据的连续语句。
results: 研究结果表明，提posed的连续词嵌入模型可以有效地利用每个参与者的专有信息和共享信息。此外，生成的文本具有与目标文本相似的相关性，BERTScore 平均值为 0.816，与之前的 fMRI 研究相当。Abstract
Decoding language from neural signals holds considerable theoretical and practical importance. Previous research has indicated the feasibility of decoding text or speech from invasive neural signals. However, when using non-invasive neural signals, significant challenges are encountered due to their low quality. In this study, we proposed a data-driven approach for decoding semantic of language from Magnetoencephalography (MEG) signals recorded while subjects were listening to continuous speech. First, a multi-subject decoding model was trained using contrastive learning to reconstruct continuous word embeddings from MEG data. Subsequently, a beam search algorithm was adopted to generate text sequences based on the reconstructed word embeddings. Given a candidate sentence in the beam, a language model was used to predict the subsequent words. The word embeddings of the subsequent words were correlated with the reconstructed word embedding. These correlations were then used as a measure of the probability for the next word. The results showed that the proposed continuous word embedding model can effectively leverage both subject-specific and subject-shared information. Additionally, the decoded text exhibited significant similarity to the target text, with an average BERTScore of 0.816, a score comparable to that in the previous fMRI study.
摘要
decode language from neural signals has important theoretical and practical significance. Previous research has shown that it is feasible to decode text or speech from invasive neural signals. However, when using non-invasive neural signals, there are significant challenges due to their low quality. In this study, we proposed a data-driven approach for decoding the semantic of language from Magnetoencephalography (MEG) signals recorded while subjects were listening to continuous speech. First, a multi-subject decoding model was trained using contrastive learning to reconstruct continuous word embeddings from MEG data. Then, a beam search algorithm was adopted to generate text sequences based on the reconstructed word embeddings. Given a candidate sentence in the beam, a language model was used to predict the subsequent words. The word embeddings of the subsequent words were correlated with the reconstructed word embedding. These correlations were then used as a measure of the probability for the next word. The results showed that the proposed continuous word embedding model can effectively leverage both subject-specific and subject-shared information. Additionally, the decoded text exhibited significant similarity to the target text, with an average BERTScore of 0.816, a score comparable to that in the previous fMRI study.
On the Relationship Between Iterated Statistical Linearization and Quasi-Newton Methods
results: 本研究还表明了IUKF和IPLF更新可以被rewrite为与QN-IEKF更新相似，即使有一个补做项。这使我们对基于统计线性化的迭代筛选算法的性能有更深刻的理解。Abstract
This letter investigates relationships between iterated filtering algorithms based on statistical linearization, such as the iterated unscented Kalman filter (IUKF), and filtering algorithms based on quasi-Newton (QN) methods, such as the QN iterated extended Kalman filter (QN-IEKF). Firstly, it is shown that the IUKF and the iterated posterior linearization filter (IPLF) can be viewed as QN algorithms, by finding a Hessian correction in the QN-IEKF such that the IPLF iterate updates are identical to that of the QN-IEKF. Secondly, it is shown that the IPLF/IUKF update can be rewritten such that it is approximately identical to the QN-IEKF, albeit for an additional correction term. This enables a richer understanding of the properties of iterated filtering algorithms based on statistical linearization.
摘要
Firstly, it is shown that the IUKF and the IPLF can be viewed as QN algorithms by finding a Hessian correction in the QN-IEKF such that the IPLF iterate updates are identical to those of the QN-IEKF.Secondly, it is shown that the IPLF/IUKF update can be rewritten so that it is approximately identical to the QN-IEKF, with an additional correction term. This provides a deeper understanding of the properties of iterated filtering algorithms based on statistical linearization.
results: 数字示例表明，不同类型的滤波器在非线性定位问题中的估计精度差异较大，标准滤波器在精度方面落后于迭代滤波器和动态迭代滤波器，但是它们在计算效率方面占据了优势。Abstract
This letter shows that the following three classes of recursive state estimation filters: standard filters, such as the extended Kalman filter; iterated filters, such as the iterated unscented Kalman filter; and dynamically iterated filters, such as the dynamically iterated posterior linearization filters; can be unified in terms of a general algorithm. The general algorithm highlights the strong similarities between specific filtering algorithms in the three filter classes and facilitates an in-depth understanding of the pros and cons of the different filter classes and algorithms. We end with a numerical example showing the estimation accuracy differences between the three classes of filters when applied to a nonlinear localization problem.
摘要
这封信件显示了以下三类 recursive state estimation 筛子可以被统一为一个通用算法：标准筛子（如扩展卡尔曼筛子）、迭代筛子（如迭代抽象卡尔曼筛子）和动态迭代筛子（如动态迭代 posterior linearization 筛子）。通用算法使得specific filtering algorithms在三个筛子类中的强相似性更加明显，并且便于深入了解每个筛子类的优缺点。我们结束了一个数值示例，表明不同类型的筛子在非线性定位问题中的估计精度差异。Note: "Simplified Chinese" is also known as "Mandarin" or "Standard Chinese".
Exact solution of the full RMSA problem in elastic optical networks
paper_authors: Fabio David, José F. de Rezende, Valmir C. Barbosa
for: solves the Routing, Modulation, and Spectrum Allocation (RMSA) problem in Elastic Optical Networks (EONs) to maximize the number of admitted demands while minimizing the number of regenerators and frequency slots used.
methods: uses a complex ILP (Integer Linear Programming) formulation that takes into account frequency-slot continuity and contiguity.
results: the formulation is applied to the NSFNET topology to demonstrate the practicality and importance of obtaining exact solutions.Abstract
Exact solutions of the Routing, Modulation, and Spectrum Allocation (RMSA) problem in Elastic Optical Networks (EONs), so that the number of admitted demands is maximized while those of regenerators and frequency slots used are minimized, require a complex ILP formulation taking into account frequency-slot continuity and contiguity. We introduce the first such formulation, ending a hiatus of some years since the last ILP formulation for a much simpler RMSA variation was introduced. By exploiting a number of problem and solver specificities, we use the NSFNET topology to illustrate the practicality and importance of obtaining exact solutions.
摘要
Routing、Modulation、和 Spectrum Allocation（RMSA）问题的精确解决方案，以最大化接受的需求数，同时最小化使用的重建器和频率槽数，需要复杂的ILP表述，考虑频率槽连续性和紧密性。我们提出了首个这种形式的表述，结束了一些年来没有新的ILP表述的停滞。通过利用一些问题和解决方案特点，我们使用NSFNETtopology示例ify了实际性和重要性获得精确解。
Fluid Antenna-Assisted Dirty Multiple Access Channels over Composite Fading
methods: 作者使用了Jakes模型和copula理论，通过Spearman的{\rho} rank correlation coefficient来准确描述FA通道之间的空间相关性，并得出了关于Fisher-Snedecor F 折射下的停机概率（OP）的关闭式表达。
results: 作者的计算结果表明，在考虑FA时，多用户通信系统的性能可以得到改善，特别是在OP和用户数量上。此外，作者还发现了可以使用只一个FA在接收器上支持大量用户，只需要几波长的空间。Abstract
This letter investigates the application of the emerging fluid antenna (FA) technology in multiuser communication systems when side information (SI) is available at the transmitters. In particular, we consider a K-user dirty multiple access channel (DMAC) with non-causally known SI at the transmitters, where K users send independent messages to a common receiver with a FA capable of changing its location depending on the channel condition. By connecting Jakes' model to copula theory through Spearman's {\rho} rank correlation coefficient, we accurately describe the spatial correlation between the FA channels, and derive a closed-form expression for the outage probability (OP) under Fisher-Snedecor F fading. Numerical results illustrate how considering FA can improve the performance of multiuser communication systems in terms of the OP and also support a large number of users using only one FA at the common receiver in a few wavelengths of space.
摘要
On Performance of Fluid Antenna System using Maximum Ratio Combining
paper_authors: Xiazhi Lai, Tuo Wu, Junteng Yao, Cunhua Pan, Maged Elkashlan, Kai-Kit Wong
for: 这个研究是 investigate a fluid antenna system (FAS) 可以同时活动多个端口，以实现更好的接收性能。
methods: 这个研究使用 maximum ratio combining (MRC) 将接收到的信号从选择的多个端口进行组合。
results: 研究结果表明，使用 FAS 可以利用各个端口的空间多样性，并且通过计算机模拟得到了证明。Abstract
This letter investigates a fluid antenna system (FAS) where multiple ports can be activated for signal combining for enhanced receiver performance. Given $M$ ports at the FAS, the best $K$ ports out of the $M$ available ports are selected before maximum ratio combining (MRC) is used to combine the received signals from the selected ports. The aim of this letter is to study the achievable performance of FAS when more than one ports can be activated. We do so by analyzing the outage probability of this setup in Rayleigh fading channels through the utilization of Gauss-Chebyshev integration, lower bound estimation, and high signal-to-noise ratio (SNR) asymptotic approximations. Our analytical results demonstrate that FAS can harness rich spatial diversity, which is confirmed by computer simulations.
摘要
这封信件研究一种流体天线系统（FAS），其中多个端口可以被激活以实现信号合并以提高接收器性能。假设有 $M$ 个端口在 FAS 中，我们需要选择最佳的 $K$ 个端口（$K \leq M$），然后使用最大比率组合（MRC）将接收到的信号从选择的端口进行组合。本信件的目的是研究 FAS 在多个端口可以被激活的情况下可以达到的性能。我们通过利用 Gaussian-Chebyshev 积分、下界估计和高 SNR 强制近似来分析 Rayleigh 抽象渐近频谱中的失业概率。我们的分析结果表明，FAS 可以利用丰富的空间多样性，这被计算仿真所证实。
A Gaussian Copula Approach to the Performance Analysis of Fluid Antenna Systems
results: 我们发现增加流体天线大小可以降低OP和DOR，但系统性能随天线端口数量增加而减退。此外，我们的结果表明FAS比单一固定天线系统具有更好的性能，即使流体天线较小。Abstract
This paper investigates the performance of a singleuser fluid antenna system (FAS), by exploiting a class of elliptical copulas to describe the structure of dependency amongst the fluid antenna ports. By expressing Jakes' model in terms of the Gaussian copula, we consider two cases: (i) the general case, i.e., any arbitrary correlated fading distribution; and (ii) the specific case, i.e., correlated Nakagami-m fading. For both scenarios, we first derive analytical expressions for the cumulative distribution function (CDF) and probability density function (PDF) of the equivalent channel in terms of multivariate normal distribution. Then, we obtain the outage probability (OP) and the delay outage rate (DOR) to analyze the performance of the FAS. By employing the popular rank correlation coefficients such as Spearman's \{rho} and Kendall's {\tau}, we measure the degree of dependency in correlated arbitrary fading channels and illustrate how the Gaussian copula can be accurately connected to Jakes' model in FAS without complicated mathematical analysis. Numerical results show that increasing the fluid antenna size provides lower OP and DOR, but the system performance saturates as the number of antenna ports increases. In addition, our results indicate that FAS provides better performance compared to conventional single-fixed antenna systems even when the size of fluid antenna is small.
摘要
A Tutorial on Environment-Aware Communications via Channel Knowledge Map for 6G
paper_authors: Yong Zeng, Junting Chen, Jie Xu, Di Wu, Xiaoli Xu, Shi Jin, Xiqi Gao, David Gesbert, Shuguang Cui, Rui Zhang
for: This paper aims to provide a comprehensive tutorial overview on environment-aware communications enabled by channel knowledge map (CKM) for 6G mobile communication networks.
methods: The paper discusses the basic concept of CKM, compares it with various existing channel inference techniques, and presents the main techniques for CKM construction, including both model-free and model-assisted approaches.
results: The paper provides a general framework for the utilization of CKM to achieve environment-aware communications and discusses typical CKM-aided communication scenarios. It also highlights important open problems in CKM research and potential solutions to inspire future work.Here’s the text in Simplified Chinese:
results: 论文提供CKM在环境意识通信中的总体框架，并介绍一些典型的CKM帮助通信场景。它还提出了importante的CKM研究开放问题，并讨论了可能的解决方案，以启发未来工作。Abstract
Sixth-generation (6G) mobile communication networks are expected to have dense infrastructures, large-dimensional channels, cost-effective hardware, diversified positioning methods, and enhanced intelligence. Such trends bring both new challenges and opportunities for the practical design of 6G. On one hand, acquiring channel state information (CSI) in real time for all wireless links becomes quite challenging in 6G. On the other hand, there would be numerous data sources in 6G containing high-quality location-tagged channel data, making it possible to better learn the local wireless environment. By exploiting such new opportunities and for tackling the CSI acquisition challenge, there is a promising paradigm shift from the conventional environment-unaware communications to the new environment-aware communications based on the novel approach of channel knowledge map (CKM). This article aims to provide a comprehensive tutorial overview on environment-aware communications enabled by CKM to fully harness its benefits for 6G. First, the basic concept of CKM is presented, and a comparison of CKM with various existing channel inference techniques is discussed. Next, the main techniques for CKM construction are discussed, including both the model-free and model-assisted approaches. Furthermore, a general framework is presented for the utilization of CKM to achieve environment-aware communications, followed by some typical CKM-aided communication scenarios. Finally, important open problems in CKM research are highlighted and potential solutions are discussed to inspire future work.
摘要
Interpretable and Efficient Beamforming-Based Deep Learning for Single Snapshot DOA Estimation
results: 根据 simulations 和实际数据集的实验结果，这种方法在准确率和计算时间方面具有优势，并且在其他深度学习DOA估计网络中表现出了更好的一致性、效率和可解释性。Abstract
We introduce an interpretable deep learning approach for direction of arrival (DOA) estimation with a single snapshot. Classical subspace-based methods like MUSIC and ESPRIT use spatial smoothing on uniform linear arrays for single snapshot DOA estimation but face drawbacks in reduced array aperture and inapplicability to sparse arrays. Single-snapshot methods such as compressive sensing and iterative adaptation approach (IAA) encounter challenges with high computational costs and slow convergence, hampering real-time use. Recent deep learning DOA methods offer promising accuracy and speed. However, the practical deployment of deep networks is hindered by their black-box nature. To address this, we propose a deep-MPDR network translating minimum power distortionless response (MPDR)-type beamformer into deep learning, enhancing generalization and efficiency. Comprehensive experiments conducted using both simulated and real-world datasets substantiate its dominance in terms of inference time and accuracy in comparison to conventional methods. Moreover, it excels in terms of efficiency, generalizability, and interpretability when contrasted with other deep learning DOA estimation networks.
摘要
我们介绍一个可解释深度学习方法来测量方向来源（DOA）的单一快照。经典的子空间基础方法如MUSIC和ESPRIT使用线性阵列上的空间平滑来进行单一快照DOA估计，但是它们受到缩小阵列范围和不适用于叠合阵列的限制。单一快照方法如压缩感知和迭代适应方法（IAA）则面临高计算成本和慢的融合速度，使其在实时使用中受到阻碍。现代深度学习DOA方法则提供了准确性和速度的推荐，但是实际应用受到黑盒子的问题所限。为了解决这个问题，我们提出了深度-MPDR网络，将最小功率无损响应（MPDR）型扁平阵列转换为深度学习，从而提高普遍性和效率。我们在使用实验和真实数据进行了全面的比较，证明了我们的方法在推理时间和准确性方面较 conventional方法优越，并且在效率、普遍性和可解释性方面也较其他深度学习DOA估计网络优越。