paper_authors: Andrea Abrardo, Alberto Toccafondi, Marco Di Renzo for:* 这篇论文主要研究的是利用多口网络理论分析和优化智能反射表面（RIS），尤其是在距离半波长之下 spacing 的情况下。methods:* 这篇论文使用了 $Z$-parameter（阻抗）和 $S$-parameter（散射）矩阵来表示 RIS 的辐射特性。* 提出了一种基于 $S$-parameter 表示的迭代算法，用于在电romagnetic 互相作用的情况下优化 RIS 的可调负载。results:* 研究发现，通过对 RIS 的结构散射进行考虑，可以更好地优化 RIS 的辐射特性，并且可以在不同的方向上获得更高的接收功率。* 对比 $Z$-parameter 和 $S$-parameter 表示，发现 $S$-parameter 更能准确地描述 RIS 的辐射特性，并且可以更快地获得更好的优化结果。Abstract
Multiport network theory has been proved to be a suitable abstraction model for analyzing and optimizing reconfigurable intelligent surfaces (RISs), especially for studying the impact of the electromagnetic mutual coupling among radiating elements that are spaced less than half of the wavelength. Both representations in terms of $Z$-parameter (impedance) and $S$-parameter (scattering) matrices are widely utilized. In this paper, we embrace multiport network theory for analyzing and optimizing the reradiation properties of RIS-aided channels, and provide four new contributions. (i) First, we offer a thorough comparison between the $Z$-parameter and $S$-parameter representations. This comparison allows us to unveil that the typical scattering models utilized for RIS-aided channels ignore the structural scattering from the RIS, which results in an unwanted specular reflection. (ii) Then, we develop an iterative algorithm for optimizing, in the presence of electromagnetic mutual coupling, the tunable loads of the RIS based on the $S$-parameters representation. We prove that small perturbations of the step size of the algorithm result in larger variations of the $S$-parameter matrix compared with the $Z$-parameter matrix, resulting in a faster convergence rate. (iii) Subsequently, we generalize the proposed algorithm to suppress the specular reflection due to the structural scattering, while maximizing the received power towards the direction of interest, and analyze the effectiveness and tradeoffs of the proposed approach. (iv) Finally, we validate the theoretical findings and algorithms with numerical simulations and a commercial full-wave electromagnetic simulator based on the method of moments.
摘要
多ports网络理论被证明是对折叠智能表面（RIS）的分析和优化模型适用，尤其是研究电磁共振元素之间的电磁共振coupling的影响。这两种表述都广泛使用$Z$-参数（阻抗）和$S$-参数（散射）矩阵。在这篇论文中，我们使用多ports网络理论分析和优化RIS-帮助通道的反射特性，并提供四项新贡献。（i）首先，我们对$Z$-参数和$S$-参数表述进行了深入的比较。这种比较表明，通常用于RIS-帮助通道的散射模型忽略了RIS的结构散射，导致不必要的反射。（ii）然后，我们开发了基于$S$-参数表述的迭代算法，用于在电磁共振coupling存在的情况下优化RIS的可变荷重。我们证明，对算法步长的小 perturbation会导致$S$-参数矩阵中的变化更大，而$Z$-参数矩阵中的变化更小，因此算法的速度更快。（iii）接着，我们扩展了提议的算法，以suppress结构散射引起的反射，同时 Maximize received power towards the direction of interest。我们分析了提议的效果和牺牲。（iv）最后，我们验证了理论发现和算法通过数值仿真和商业全波电磁 simulator based on the method of moments。
Generative AI for Space-Air-Ground Integrated Networks (SAGIN)
results: 根据实验结果，提出的框架能够提高SAGIN的服务质量。此外，本文还讨论了将来的生成AI-enabled SAGIN研究方向。Abstract
Recently, generative AI technologies have emerged as a significant advancement in artificial intelligence field, renowned for their language and image generation capabilities. Meantime, space-air-ground integrated network (SAGIN) is an integral part of future B5G/6G for achieving ubiquitous connectivity. Inspired by this, this article explores an integration of generative AI in SAGIN, focusing on potential applications and case study. We first provide a comprehensive review of SAGIN and generative AI models, highlighting their capabilities and opportunities of their integration. Benefiting from generative AI's ability to generate useful data and facilitate advanced decision-making processes, it can be applied to various scenarios of SAGIN. Accordingly, we present a concise survey on their integration, including channel modeling and channel state information (CSI) estimation, joint air-space-ground resource allocation, intelligent network deployment, semantic communications, image extraction and processing, security and privacy enhancement. Next, we propose a framework that utilizes a Generative Diffusion Model (GDM) to construct channel information map to enhance quality of service for SAGIN. Simulation results demonstrate the effectiveness of the proposed framework. Finally, we discuss potential research directions for generative AI-enabled SAGIN.
摘要
最近，生成式人工智能技术在人工智能领域取得了重要进步，被广泛应用于语言和图像生成等领域。同时，空天地三合一网络（SAGIN）是未来5G/6G的重要组成部分，旨在实现无限连接。以此为启发，本文探讨了生成式人工智能在SAGIN中的 интеграцию，主要强调其应用前景和实践案例。我们首先提供了SAGIN和生成式人工智能模型的全面审视，探讨它们的可能的 интеграción和应用前景。生成式人工智能可以生成有用的数据，并促进高级决策过程，因此可以应用于SAGIN多种场景。在这些应用场景中，我们提出了一种基于生成扩散模型（GDM）的框架，用于提高SAGIN的质量服务。实验结果表明该框架的效果是可靠的。最后，我们讨论了生成式人工智能在SAGIN中的未来研究方向。
Semantic-aware Sampling and Transmission in Energy Harvesting Systems: A POMDP Approach
results: 研究人员通过解决一个随机控制问题，实现了三个semantic-aware指标的共同优化：一、信息年龄（AoI），二、通信质量，三、错误信息年龄（AoII）。通过仿真实验，研究人员发现了优化策略的性能提升，并发现了不同的 switching-type 优化策略。Abstract
We study real-time tracking problem in an energy harvesting system with a Markov source under an imperfect channel. We consider both sampling and transmission costs and different from most prior studies that assume the source is fully observable, the sampling cost renders the source unobservable. The goal is to jointly optimize sampling and transmission policies for three semantic-aware metrics: i) the age of information (AoI), ii) general distortion, and iii) the age of incorrect information (AoII). To this end, we formulate and solve a stochastic control problem. Specifically, for the AoI metric, we cast a Markov decision process (MDP) problem and solve it using relative value iteration (RVI). For the distortion and AoII metrics, we utilize the partially observable MDP (POMDP) modeling and leverage the notion of belief MDP formulation of POMDP to find optimal policies. For the distortion metric and the AoII metric under the perfect channel setup, we effectively truncate the corresponding belief space and solve an MDP problem using RVI. For the general setup, a deep reinforcement learning policy is proposed. Through simulations, we demonstrate significant performance improvements achieved by the derived policies. The results reveal various switching-type structures of optimal policies and show that a distortion-optimal policy is also AoII optimal.
摘要
我们研究实时跟踪问题在能量收集系统中，其中源是Markov过程，并且通信频道存在不完美性。我们考虑了抽样和传输成本，并且不同于大多数前一些研究，源不可见。我们的目标是同时优化抽样和传输策略，以达到三个semantic-aware指标的最优化：一、信息年龄（AoI），二、通信误差，三、错误信息年龄（AoII）。为此，我们设计了一个随机控制问题，并使用相对价值迭代（RVI）解决Markov决策过程（MDP）问题。对于AoI指标，我们使用POMDP模型和信念MDP形式进行解决。对于误差指标和AoII指标在完美通信设置下，我们有效地舒缩相应的信念空间，并使用RVI解决MDP问题。在总体设置下，我们提议了深度强化学习策略。通过sime simulations，我们发现derived策略具有显著的性能改进。结果显示了不同的 switching-type结构，并证明了误差优化策略也是AoII优化的。
Sum-Rate Optimization for RIS-Aided Multiuser Communications with Movable Antenna
paper_authors: Yunan Sun, Hao Xu, Chongjun Ouyang, Hongwen Yang
for: 本研究旨在提高无线通信网络性能，探讨了可程度智能表面（RIS）技术的应用。
methods: 本文提出了一个基于RIS的多用户通信系统，利用可动天线（MA）技术优化通道容量。
results: 提出的迭代算法可以优化照明、RIS的反射系数（RC）值和MA的位置，以提高系统的总资料率。numerical results显示了提案的方法的有效性和MA-based系统在总资料率方面的优势。Abstract
Reconfigurable intelligent surface (RIS) is known as a promising technology to improve the performance of wireless communication networks, which has been extensively studied. Movable antenna (MA) is a novel technology that fully exploits the antenna position for enhancing the channel capacity. In this paper, we propose a new RIS-aided multiuser communication system with MAs. The sum-rate is maximized by jointly optimizing the beamforming, the reflection coefficient (RC) values of RIS and the positions of MAs. A fractional programming-based iterative algorithm is proposed to solve the formulated non-convex problem, considering three assumptions for the RIS. Numerical results are presented to verify the effectiveness of the proposed algorithm and the superiority of the proposed MA-based system in terms of sum-rate.
摘要
改进无线通信网络性能的可 configurable智能表面（RIS）技术已经广泛研究， movable antenna（MA）是一种新的技术，它可以全面利用天线位置来提高通信频率。在这篇论文中，我们提议一种基于RIS的多用户通信系统，并使用MA来提高系统性能。我们使用一种基于分数编程的迭代算法来最大化宽扩权（beamforming）、RIS反射系数（RC）和MA位置的优化问题。我们对问题进行了非几何化处理，并根据RIS的三个假设进行了解释。我们通过数值结果验证了我们的提案的有效性和MA基本系统的提高性。
Semantic Communication for Cooperative Perception based on Importance Map
methods: 本 paper 使用了一种Importance Map 技术来提取 semantic information，并提出了一种新的 Cooperative Perception Semantic Communication Scheme with Intermediate Fusion。
results: simulations 表明，我们的提议的模型在不同的通道模型下表现出了优于传统分离源-通道编码的性能。此外，我们的模型还能够在时变 multipath 拍抄频道下保持robustness。Abstract
Cooperative perception, which has a broader perception field than single-vehicle perception, has played an increasingly important role in autonomous driving to conduct 3D object detection. Through vehicle-to-vehicle (V2V) communication technology, various connected automated vehicles (CAVs) can share their sensory information (LiDAR point clouds) for cooperative perception. We employ an importance map to extract significant semantic information and propose a novel cooperative perception semantic communication scheme with intermediate fusion. Meanwhile, our proposed architecture can be extended to the challenging time-varying multipath fading channel. To alleviate the distortion caused by the time-varying multipath fading, we adopt explicit orthogonal frequency-division multiplexing (OFDM) blocks combined with channel estimation and channel equalization. Simulation results demonstrate that our proposed model outperforms the traditional separate source-channel coding over various channel models. Moreover, a robustness study indicates that only part of semantic information is key to cooperative perception. Although our proposed model has only been trained over one specific channel, it has the ability to learn robust coded representations of semantic information that remain resilient to various channel models, demonstrating its generality and robustness.
摘要
合作感知，具有更广泛的感知范围 than single-vehicle perception，在自动驾驶中扮演着越来越重要的角色，以实现3D对象探测。通过自动汽车之间的通信技术（V2V），不同的相连自动汽车（CAVs）可以共享它们的感知信息（LiDAR点云）进行合作感知。我们使用重要度图 Extract significant semantic information and propose a novel cooperative perception semantic communication scheme with intermediate fusion. Meanwhile, our proposed architecture can be extended to the challenging time-varying multipath fading channel. To alleviate the distortion caused by the time-varying multipath fading, we adopt explicit orthogonal frequency-division multiplexing (OFDM) blocks combined with channel estimation and channel equalization. Simulation results demonstrate that our proposed model outperforms the traditional separate source-channel coding over various channel models. Moreover, a robustness study indicates that only part of semantic information is key to cooperative perception. Although our proposed model has only been trained over one specific channel, it has the ability to learn robust coded representations of semantic information that remain resilient to various channel models, demonstrating its generality and robustness.Here's the translation in Traditional Chinese:合作感知，具有更广泛的感知范围 than single-vehicle perception，在自动驾驶中扮演着越来越重要的角色，以实现3D对象探测。通过自动汽车之间的通信技术（V2V），不同的相连自动汽车（CAVs）可以共享它们的感知信息（LiDAR点云）进行合作感知。我们使用重要度图 Extract significant semantic information and propose a novel cooperative perception semantic communication scheme with intermediate fusion. Meanwhile, our proposed architecture can be extended to the challenging time-varying multipath fading channel. To alleviate the distortion caused by the time-varying multipath fading, we adopt explicit orthogonal frequency-division multiplexing (OFDM) blocks combined with channel estimation and channel equalization. Simulation results demonstrate that our proposed model outperforms the traditional separate source-channel coding over various channel models. Moreover, a robustness study indicates that only part of semantic information is key to cooperative perception. Although our proposed model has only been trained over one specific channel, it has the ability to learn robust coded representations of semantic information that remain resilient to various channel models, demonstrating its generality and robustness.