paper_authors: William W. Howard, Samuel R. Shebert, Benjamin H. Kirk, R. Michael Buehrer
For: The paper proposes a cognitive radar network that leverages the adaptability of cognitive radar networks to trade between active radar observation and passive signal parameter estimation, and learns the optimal action choices for each type of target.* Methods: The paper uses a multi-armed bandit model with current class information as prior information to select between available actions, and estimates the physical behavior of targets through radar emissions when the active radar action is selected, and estimates the radio behavior of targets through passive sensing when the passive action is selected.* Results: The network collects observed behavior of targets and forms clusters of similarly-behaved targets, and meta-learns the target class distributions while learning the optimal mode selections for each target class.Here are the three points in Simplified Chinese text:* For: 该 paper 提出了一种基于认知雷达网络的方法，以便在不同的目标类型下选择最佳的行动。* Methods: 该 paper 使用了一种多重武器模型，并使用当前类信息作为先验信息来选择可用的行动。当选择活动雷达时，节点通过雷达发射来估计目标的物理行为；当选择被动时，节点通过感知来估计目标的电磁行为。* Results: 网络通过收集目标的行为观察并组织类似目标的集群，从而meta-学习目标类型分布，同时学习每个目标类型的优化模式选择。Abstract
Cognitive Radar Networks were proposed by Simon Haykin in 2006 to address problems with large legacy radar implementations - primarily, single-point vulnerabilities and lack of adaptability. This work proposes to leverage the adaptability of cognitive radar networks to trade between active radar observation, which uses high power and risks interception, and passive signal parameter estimation, which uses target emissions to gain side information and lower the power necessary to accurately track multiple targets. The goal of the network is to learn over many target tracks both the characteristics of the targets as well as the optimal action choices for each type of target. In order to select between the available actions, we utilize a multi-armed bandit model, using current class information as prior information. When the active radar action is selected, the node estimates the physical behavior of targets through the radar emissions. When the passive action is selected, the node estimates the radio behavior of targets through passive sensing. Over many target tracks, the network collects the observed behavior of targets and forms clusters of similarly-behaved targets. In this way, the network meta-learns the target class distributions while learning the optimal mode selections for each target class.
摘要
cognitive radar networks 由谢韦金（Simon Haykin）在2006年提出，以解决传统雷达实施中的单点漏洞和不可靠性问题。这项工作提议利用智能雷达网络的适应性，在高功率和风险 intercept 的 aktive雷达观测和低功率的 passive信号参数估算之间进行交换。网络的目标是通过多个目标轨迹学习target的特征和最佳行为选择。为选择可用的行动，我们使用多重武器模型，使用当前类信息作为先验信息。当选择 active雷达动作时，节点估算目标的物理行为通过雷达发射。当选择 passive动作时，节点估算目标的电磁行为通过被动探测。在许多目标轨迹中，网络收集了目标的观测行为，并将其分为类似目标类型的集群。这样，网络可以meta-学习目标类型的分布，同时学习每个目标类型的优化模式选择。
paper_authors: Ezgi Ozyilkan, Johannes Ballé, Elza Erkip
for: 这种研究是为了解决分布式源编码中的吞吐率问题，具体来说是威纳-赫茨问题。
methods: 这种研究使用机器学习的方法，特别是变量量量化，来实现数据驱动的压缩方案。
results: 研究发现，使用这种数据驱动的压缩方案可以Recover一些理想的理论解的特点，如源空间中的分割和使用侧 информацию进行最优的组合。这些行为 emerge although 没有直接使用源分布的知识。Abstract
We consider lossy compression of an information source when the decoder has lossless access to a correlated one. This setup, also known as the Wyner-Ziv problem, is a special case of distributed source coding. To this day, practical approaches for the Wyner-Ziv problem have neither been fully developed nor heavily investigated. We propose a data-driven method based on machine learning that leverages the universal function approximation capability of artificial neural networks. We find that our neural network-based compression scheme, based on variational vector quantization, recovers some principles of the optimum theoretical solution of the Wyner-Ziv setup, such as binning in the source space as well as optimal combination of the quantization index and side information, for exemplary sources. These behaviors emerge although no structure exploiting knowledge of the source distributions was imposed. Binning is a widely used tool in information theoretic proofs and methods, and to our knowledge, this is the first time it has been explicitly observed to emerge from data-driven learning.
摘要
我们考虑在损失压缩的资料来源中进行损失less压缩，当decoder有无损失的存取相关的一来。这个设置称为吴纽-兹维问题，是分布式源码编码的特殊情况。至今为止，实用的方法 для吴纽-兹维问题仍未被完全开发或严重调查。我们提议一个基于机器学习的数据驱动方法，利用人工神经网络的通用函数近似能力。我们发现，我们的神经网络压缩方案，基于可变量化，可以重新现出一些吴纽-兹维问题的理想解答，例如在源空间中的binning以及对于副信息的优化 комбина�tion。这些行为 emerge，即使没有采用知情源分布的结构化知识。binning是信息论中广泛使用的工具，而且，根据我们所知，这是第一次由数据驱动学习中明示地观察到这种行为。
How to Extend 3D GBSM to Integrated Sensing and Communication Channel with Sharing Feature?
paper_authors: Yameng Liu, Jianhua Zhang, Yuxiang Zhang, Huiwen Gong, Tao Jiang, Guangyi Liu
for: This paper is written to support the development of Integrated Sensing and Communication (ISAC) technology in 6G systems, specifically by extending the existing 3D Geometry-Based Stochastic Model (GBSM) to include sensing channels.
methods: The paper proposes a new ISAC channel model that captures the sharing feature of both communication and sensing channels, including shared scatterers, clusters, paths, and similar propagation parameters. The model is based on a cascade of TX-target, radar cross section, and target-RX, with a novel parameter S for shared target extraction.
results: The proposed ISAC channel implementation framework offers flexible configuration of sharing feature and the joint generation of communication and sensing channels, and is compatible with the 3GPP standards, offering promising support for ISAC technology evaluation.Abstract
Integrated Sensing and Communication (ISAC) is a promising technology in 6G systems. The existing 3D Geometry-Based Stochastic Model (GBSM), as standardized for 5G systems, addresses solely communication channels and lacks consideration of the integration with sensing channel. Therefore, this letter extends 3D GBSM to support ISAC research, with a particular focus on capturing the sharing feature of both channels, including shared scatterers, clusters, paths, and similar propagation param-eters, which have been experimentally verified in the literature. The proposed approach can be summarized as follows: Firstly, an ISAC channel model is proposed, where shared and non-shared components are superimposed for both communication and sensing. Secondly, sensing channel is characterized as a cascade of TX-target, radar cross section, and target-RX, with the introduction of a novel parameter S for shared target extraction. Finally, an ISAC channel implementation framework is proposed, allowing flexible configuration of sharing feature and the joint generation of communication and sensing channels. The proposed ISAC channel model can be compatible with the 3GPP standards and offers promising support for ISAC technology evaluation.
摘要
《集成感知通信（ISAC）技术在6G系统中具有极大潜力。现有的3DGeometry-Based Stochastic Model（GBSM），为5G系统制定的标准，仅考虑了通信频道，不考虑感知频道的integration。因此，本文extend GBSM，以支持ISAC研究，特别是捕捉两个频道之间的共享特征，包括共享雷达目标、群集、路径和相似的传播参数，这些参数在文献中经过实验验证。 proposeapproach可以概括为以下三个步骤：1. 建立ISAC通信频道模型，其中共享和非共享组成部分相互重叠。2. 描述感知频道为TX-目标、雷达cross section和目标-RX的链式，并引入一个新参数S，用于捕捉共享目标。3. 提出ISAC通信频道实现框架，允许共享特征的灵活配置和共同生成通信和感知频道。提议的ISAC通信频道模型可以与3GPP标准兼容，并且对ISAC技术评估具有极大潜力。
Spherical Wavefront Near-Field DoA Estimation in THz Automotive Radar
results: numerical experiments表明该方法可以准确地估计目标参数。Abstract
Automotive radar at terahertz (THz) band has the potential to provide compact design. The availability of wide bandwidth at THz-band leads to high range resolution. Further, very narrow beamwidth arising from large arrays yields high angular resolution up to milli-degree level direction-of-arrival (DoA) estimation. At THz frequencies and extremely large arrays, the signal wavefront is spherical in the near-field that renders traditional far-field DoA estimation techniques unusable. In this work, we examine near-field DoA estimation for THz automotive radar. We propose an algorithm using multiple signal classification (MUSIC) to estimate target DoAs and ranges while also taking beam-squint in near-field into account. Using an array transformation approach, we compensate for near-field beam-squint in noise subspace computations to construct the beam-squint-free MUSIC spectra. Numerical experiments show the effectiveness of the proposed method to accurately estimate the target parameters.
摘要
自动驱动radar在tera哈勒tz（THz）频带有可能提供更加紧凑的设计。 THz频带的宽频率导致高分辨率范围。此外，非常窄的扫描幅由大型阵列产生，使得高度分辨率的方向来源估计（DoA）。在THz频率和极其大的阵列下，信号波front在近场是球形的，使得传统的远场DoA估计技术无法使用。在这种情况下，我们研究了THz自动驱动radar的近场DoA估计。我们提出了使用多个信号分类（MUSIC）算法来估计目标DoAs和距离，同时也考虑近场扫描幅的影响。使用阵列变换方法，我们在噪声空间计算中补做近场扫描幅的影响，构建了扫描幅自由的MUSIC谱。 numerically experiments show the effectiveness of the proposed method to accurately estimate the target parameters.Note: The translation is in Simplified Chinese, which is the standard form of Chinese used in mainland China and Singapore. If you need Traditional Chinese, please let me know.
Power Optimization in Satellite Communication Using Multi-Intelligent Reflecting Surfaces
results: 研究发现这两个方法可以实现卫星到地面通信系统的能源效率提高，并且在实际运行中可以实现可 COUNTING 的能源储存。Abstract
This study introduces two innovative methodologies aimed at augmenting energy efficiency in satellite-to-ground communication systems through the integration of multiple Reflective Intelligent Surfaces (RISs). The primary objective of these methodologies is to optimize overall energy efficiency under two distinct scenarios. In the first scenario, denoted as Ideal Environment (IE), we enhance energy efficiency by decomposing the problem into two sub-optimal tasks. The initial task concentrates on maximizing power reception by precisely adjusting the phase shift of each RIS element, followed by the implementation of Selective Diversity to identify the RIS element delivering maximal power. The second task entails minimizing power consumption, formulated as a binary linear programming problem, and addressed using the Binary Particle Swarm Optimization (BPSO) technique. The IE scenario presupposes an environment where signals propagate without any path loss, serving as a foundational benchmark for theoretical evaluations that elucidate the systems optimal capabilities. Conversely, the second scenario, termed Non-Ideal Environment (NIE), is designed for situations where signal transmission is subject to path loss. Within this framework, the Adam algorithm is utilized to optimize energy efficiency. This non ideal setting provides a pragmatic assessment of the systems capabilities under conventional operational conditions. Both scenarios emphasize the potential energy savings achievable by the satellite RIS system. Empirical simulations further corroborate the robustness and effectiveness of our approach, highlighting its potential to enhance energy efficiency in satellite-to-ground communication systems.
摘要
Pilot-Based Uplink Power Control in Single-UE Massive MIMO Systems With 1-Bit ADCs
results: 比较conventional closed-loop上行功率控制方法，提出的方法具有更高的精度和更好的性能。Abstract
We propose uplink power control (PC) methods for massive multiple-input multiple-output systems with 1-bit analog-to-digital converters, which are specifically tailored to address the non-monotonic data detection performance with respect to the transmit power of the user equipment (UE). Considering a single UE, we design a multi-amplitude pilot sequence to capture the aforementioned non-monotonicity, which is utilized at the base station to derive UE transmit power adjustments via single-shot or differential power control (DPC) techniques. Both methods enable closed-loop uplink PC using different feedback approaches. The single-shot method employs one-time multi-bit feedback, while the DPC method relies on continuous adjustments with 1-bit feedback. Numerical results demonstrate the superiority of the proposed schemes over conventional closed-loop uplink PC techniques.
摘要
我们提出了大量多输入多 outputs系统中的上传功率控制（PC）方法，特别是为了解决用户设备（UE）的传输功率与数据探测性的非单对数关系。对于单一UE，我们设计了多极性导航序列来捕捉上述非单对数关系，这些序列在基站端被用来 derivUE传输功率调整 via 单一射击或差分功率控制（DPC）技术。这两种方法均允许关闭loop上传PC使用不同的反馈方法。单一射击方法使用一次多位反馈，而DPC方法则靠 Continuous adjustments with 1-bit feedback。数字结果显示我们的提案方案比于传统关闭loop上传PC技术更有优势。
Terahertz-Enpowered Communications and Sensing in 6G Systems: Opportunities and Challenges
results: 论文未提出具体的结果，主要是为了探讨6G系统中THz频段的可能性和挑战。Abstract
The current focus of academia and the telecommunications industry has been shifted to the development of the six-generation (6G) cellular technology, also formally referred to as IMT-2030. Unprecedented applications that 6G aims to accommodate demand extreme communications performance and, in addition, disruptive capabilities such as network sensing. Recently, there has been a surge of interest in terahertz (THz) frequencies as it offers not only massive spectral resources for communication but also distinct advantages in sensing, positioning, and imaging. The aim of this paper is to provide a brief outlook on opportunities opened by this under-exploited band and challenges that must be addressed to materialize the potential of THz-based communications and sensing in 6G systems.
摘要
现在学术界和电信产业的焦点已经转移到第六代（6G）无线技术的开发，即IMT-2030。6G旨在满足极高通信性能的应用需求，同时还具有破坏性能，如网络感知。最近，人们对tera兆赫兹（THz）频率的利用表现出了很大的兴趣，因为它不仅提供了巨大的频率资源 для通信，而且在感知、定位和成像方面具有明显的优势。本文的目的是提供6G系统中THz频率的可能性和挑战的简要预测。
Transmitting Data Through Reconfigurable Intelligent Surface: A Spatial Sigma-Delta Modulation Approach
results: 该论文的实验结果显示，使用Sigma-Delta干扰模ulasi可以实现与不量化ZF方案相同的比特错误率性能。Abstract
Transmitting data using the phases on reconfigurable intelligent surfaces (RIS) is a promising solution for future energy-efficient communication systems. Recent work showed that a virtual phased massive multiuser multiple-input-multiple-out (MIMO) transmitter can be formed using only one active antenna and a large passive RIS. In this paper, we are interested in using such a system to perform MIMO downlink precoding. In this context, we may not be able to apply conventional MIMO precoding schemes, such as the simple zero-forcing (ZF) scheme, and we typically need to design the phase signals by solving optimization problems with constant modulus constraints or with discrete phase constraints, which pose challenges with high computational complexities. In this work, we propose an alternative approach based on Sigma-Delta ($\Sigma\Delta$) modulation, which is classically famous for its noise-shaping ability. Specifically, first-order $\Sigma\Delta$ modulation is applied in the spatial domain to handle phase quantization in generating constant envelope signals. Under some mild assumptions, the proposed phased $\Sigma\Delta$ modulator allows us to use the ZF scheme to synthesize the RIS reflection phases with negligible complexity. The proposed approach is empirically shown to achieve comparable bit error rate performance to the unquantized ZF scheme.
摘要
通过可重新配置智能表面（RIS）传输数据是未来能效通信系统的承诺之一。最近的研究表明，只需一个活动天线和一大串pascal RIS可以形成虚拟 phase massive MIMO发射器。在这篇论文中，我们关心使用这种系统来执行MIMO下降干扰。在这种情况下，我们通常无法采用传统的MIMO预处理方案，如简单的零偏置（ZF）方案，而是需要设计相位信号通过优化问题的解决，这会带来高计算复杂度的挑战。在这种情况下，我们提议使用Sigma-Delta（$\Sigma\Delta$)模ulation，这是经典知名的噪声定向技术。 Specifically, we apply first-order $\Sigma\Delta$ modulation in the spatial domain to handle phase quantization in generating constant envelope signals. Under some mild assumptions, the proposed phased $\Sigma\Delta$ modulator allows us to use the ZF scheme to synthesize the RIS reflection phases with negligible complexity. The proposed approach is empirically shown to achieve comparable bit error rate performance to the unquantized ZF scheme.