Information Theory

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New submissions (showing 5 of 5 entries )

[1] arXiv:2509.19572 [cn-pdf, pdf, html, other]

Title: Analyzing α-divergence in Gaussian Rate-Distortion-Perception Theory Show Chinese title

Title: 分析高斯率失真感知理论中的α散度

Martha V. Sourla, Giuseppe Serra, Photios A. Stavrou, Marios Kountouris

Comments: conference, 5 pages, 3 figures

Journal-ref: 2024 IEEE 25th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

Subjects: Information Theory (cs.IT)

The problem of estimating the information rate distortion perception function (RDPF), which is a relevant information-theoretic quantity in goal-oriented lossy compression and semantic information reconstruction, is investigated here. Specifically, we study the RDPF tradeoff for Gaussian sources subject to a mean-squared error (MSE) distortion and a perception measure that belongs to the family of {\alpha} divergences. Assuming a jointly Gaussian RDPF, which forms a convex optimization problem, we characterize an upper bound for which we find a parametric solution. We show that evaluating the optimal parameters of this parametric solution is equivalent to finding the roots of a reduced exponential polynomial of degree {\alpha}. Additionally, we determine which disjoint sets contain each root, which enables us to evaluate them numerically using the well-known bisection method. Finally, we validate our analytical findings with numerical results and establish connections with existing results. Show Chinese abstract

此处研究了估计信息率失真感知函数（RDPF）的问题，这是目标导向的有损压缩和语义信息重建中的一个相关信息理论量。 具体而言，我们研究了在均方误差（MSE）失真和属于{\alpha }散度族的感知度量约束下的高斯信源的 RDPF 折衷。 假设 RDPF 是联合高斯的，这构成了一个凸优化问题，我们表征了一个上界，并找到了一个参数解。 我们证明了评估该参数解的最优参数等价于求解一个次数为{\alpha }的约简指数多项式的根。 此外，我们确定了每个根所在的不相交集合，这使我们能够使用众所周知的二分法数值求解。 最后，我们通过数值结果验证了我们的分析结果，并建立了与现有结果的联系。

[2] arXiv:2509.19598 [cn-pdf, pdf, html, other]

Title: Efficient $\varepsilon$-approximate minimum-entropy couplings Show Chinese title

Title: 高效的$\varepsilon$-近似最小熵耦合

Spencer Compton

Subjects: Information Theory (cs.IT) ; Data Structures and Algorithms (cs.DS)

Given $m \ge 2$ discrete probability distributions over $n$ states each, the minimum-entropy coupling is the minimum-entropy joint distribution whose marginals are the same as the input distributions. Computing the minimum-entropy coupling is NP-hard, but there has been significant progress in designing approximation algorithms; prior to this work, the best known polynomial-time algorithms attain guarantees of the form $H(\operatorname{ALG}) \le H(\operatorname{OPT}) + c$, where $c \approx 0.53$ for $m=2$, and $c \approx 1.22$ for general $m$ [CKQGK '23]. A main open question is whether this task is APX-hard, or whether there exists a polynomial-time approximation scheme (PTAS). In this work, we design an algorithm that produces a coupling with entropy $H(\operatorname{ALG}) \le H(\operatorname{OPT}) + \varepsilon$ in running time $n^{O(\operatorname{poly}(1/\varepsilon) \cdot \operatorname{exp}(m) )}$: showing a PTAS exists for constant $m$. Show Chinese abstract

给定 $m \ge 2$个在 $n$个状态上的离散概率分布，最小熵耦合是具有与输入分布相同的边缘分布的最小熵联合分布。 计算最小熵耦合是NP难的，但设计近似算法已经取得了显著进展；在此工作之前，已知的最佳多项式时间算法的保证形式为 $H(\operatorname{ALG}) \le H(\operatorname{OPT}) + c$，其中 $c \approx 0.53$ 对于 $m=2$，而 $c \approx 1.22$ 对于一般的 $m$ [CKQGK '23]。 一个主要的开放问题是，这个任务是否是APX难的，或者是否存在一个多项式时间近似方案（PTAS）。 在本工作中，我们设计了一个算法，在运行时间$n^{O(\operatorname{poly}(1/\varepsilon) \cdot \operatorname{exp}(m) )}$内生成一个熵为$H(\operatorname{ALG}) \le H(\operatorname{OPT}) + \varepsilon$的耦合，证明了对于常数$m$存在一个多项式时间近似方案。

[3] arXiv:2509.19791 [cn-pdf, pdf, html, other]

Title: Agentic AI for Low-Altitude Semantic Wireless Networks: An Energy Efficient Design Show Chinese title

Title: 面向低空语义无线网络的代理人工智能：一种高效节能设计

Zhouxiang Zhao, Ran Yi, Yihan Cang, Boyang Jin, Zhaohui Yang, Mingzhe Chen, Chongwen Huang, Zhaoyang Zhang

Subjects: Information Theory (cs.IT)

This letter addresses the energy efficiency issue in unmanned aerial vehicle (UAV)-assisted autonomous systems. We propose a framework for an agentic artificial intelligence (AI)-powered low-altitude semantic wireless network, that intelligently orchestrates a sense-communicate-decide-control workflow. A system-wide energy consumption minimization problem is formulated to enhance mission endurance. This problem holistically optimizes key operational variables, including UAV's location, semantic compression ratio, transmit power of the UAV and a mobile base station, and binary decision for AI inference task offloading, under stringent latency and quality-of-service constraints. To tackle the formulated mixed-integer non-convex problem, we develop a low-complexity algorithm which can obtain the globally optimal solution with two-dimensional search. Simulation results validate the effectiveness of our proposed design, demonstrating significant reductions in total energy consumption compared to conventional baseline approaches. Show Chinese abstract

这封信件讨论了无人机（UAV）辅助自主系统中的能效问题。 我们提出了一种基于代理人工智能（AI）的低空语义无线网络框架，该框架智能地协调感知-通信-决策-控制的工作流程。 制定一个系统范围内的能耗最小化问题，以提高任务续航能力。 该问题全面优化关键操作变量，包括无人机的位置、语义压缩比、无人机和移动基站的发射功率，以及AI推理任务卸载的二进制决策，在严格的时延和服务质量约束下。 为解决所提出的混合整数非凸问题，我们开发了一种低复杂度算法，可以通过二维搜索获得全局最优解。 仿真结果验证了我们所提出设计的有效性，表明与传统基线方法相比，总能耗显著减少。

[4] arXiv:2509.19910 [cn-pdf, pdf, other]

Title: Understanding the ratio of the partition sum to its Bethe approximation via double covers Show Chinese title

Title: 通过双覆盖理解划分和与其Bethe近似的比值

Pascal O. Vontobel

Comments: Extended version (including appendices) of a paper appearing in Proc. 2025 IEEE Information Theory Workshop, Sydney, Australia, Sept./Oct., 2025

Subjects: Information Theory (cs.IT) ; Combinatorics (math.CO) ; Statistics Theory (math.ST)

For various classes of graphical models it has been observed that the ratio of the partition sum to its Bethe approximation is often close to being the square of the ratio of the partition sum to its degree-2 Bethe approximation. This is of relevance because the latter ratio can often better be analyzed and/or quantified than the former ratio. In this paper, we give some justifications for the observed relationship between these two ratios and then analyze these ratios for two classes of log-supermodular graphical models. Show Chinese abstract

对于各种类型的图形模型，观察到分割和与其Bethe近似值的比值通常接近于分割和其度为2的Bethe近似值的比值的平方。 这具有相关性，因为后者比值通常更容易分析和/或量化。 在本文中，我们对观察到的这两个比值之间的关系提供了一些证明，然后分析了两种类型的对数超模图形模型中的这些比值。

[5] arXiv:2509.20092 [cn-pdf, pdf, html, other]

Title: Constrained Higher-Order Binary Optimization for Wireless Communications Systems Using Ising Machines Show Chinese title

Title: 基于伊辛机的无线通信系统约束高阶二元优化

Gan Zheng, Ioannis Krikidis

Comments: to appear in IEEE Transactions on Wireless Communications

Subjects: Information Theory (cs.IT)

This paper develops an algorithmic solution using Ising machines to solve large-scale higher-order binary optimization (HOBO) problems with inequality constraints for resource optimization in wireless communications systems. Quadratic unconstrained binary optimization (QUBO) aims to solve a special category of these problems widely encountered in engineering and science. To solve QUBO instances, specialized Ising machines have been designed, while sophisticated quantum annealing algorithm and quantum-inspired classical heuristics have been developed. However, the application of QUBO in wireless communications has limited practical interest mainly due to the complexity of resource optimization problems which are often characterized by high-order polynomial terms and strict inequality constraints. To overcome these bottlenecks and take advantage of recent advancements in Ising machines, in this paper, we propose an iterative algorithmic solution to solve HOBO problems, which is based on the augmented Lagrangian method to handle constraints. Specifically, Taylor expansion is employed to approximate higher-order polynomials to quadratic ones in the augmented Lagrangian function, which enables the solution of a single QUBO problem at each iteration without auxiliary variables. As an illustrative case study, we consider the problem of phase optimization in a simultaneous wireless information and power transfer system, where a reconfigurable intelligent surface with 1-bit phase resolution is used to facilitate information/energy transfer. Simulation results verify that the proposed algorithm achieves satisfactory performance and outperforms heuristic benchmark schemes. Show Chinese abstract

本文开发了一种基于伊辛机的算法解决方案，用于解决无线通信系统中资源优化的大规模高阶二元优化（HOBO）问题，这些问题是带有不等式约束的。二次无约束二元优化（QUBO）旨在解决在工程和科学中广泛遇到的这类问题的一个特殊类别。为了解决QUBO实例，已经设计了专门的伊辛机，同时开发了复杂的量子退火算法和受量子启发的经典启发式方法。然而，由于资源优化问题的复杂性，通常由高阶多项式项和严格的不等式约束所表征，QUBO在无线通信中的应用具有有限的实际兴趣。为了克服这些瓶颈并利用伊辛机的最新进展，本文提出了一种迭代算法解决方案来解决HOBO问题，该方案基于增广拉格朗日方法来处理约束。具体而言，采用泰勒展开将增广拉格朗日函数中的高阶多项式近似为二次形式，这使得在每次迭代中无需辅助变量即可解决单个QUBO问题。作为示例案例研究，我们考虑了同时无线信息和功率传输系统中的相位优化问题，其中使用具有1位相位分辨率的可重构智能表面来促进信息/能量传输。仿真结果验证了所提出的算法实现了令人满意的性能，并优于启发式基准方案。

Cross submissions (showing 9 of 9 entries )

[6] arXiv:2509.19306 (cross-list from eess.SP) [cn-pdf, pdf, html, other]

Title: A Federated Fine-Tuning Paradigm of Foundation Models in Heterogenous Wireless Networks Show Chinese title

Title: 在异构无线网络中基础模型的联邦微调范式

Jingyi Wang, Zhongyuan Zhao, Qingtian Wang, Zexu Li, Yue Wang, Tony Q. S. Quek

Subjects: Signal Processing (eess.SP) ; Artificial Intelligence (cs.AI) ; Information Theory (cs.IT) ; Networking and Internet Architecture (cs.NI)

Edge intelligence has emerged as a promising strategy to deliver low-latency and ubiquitous services for mobile devices. Recent advances in fine-tuning mechanisms of foundation models have enabled edge intelligence by integrating low-rank adaptation (LoRA) with federated learning. However, in wireless networks, the device heterogeneity and resource constraints on edge devices pose great threats to the performance of federated fine-tuning. To tackle these issues, we propose to optimize federated fine-tuning in heterogenous wireless networks via online learning. First, the framework of switching-based federated fine-tuning in wireless networks is provided. The edge devices switches to LoRA modules dynamically for federated fine-tuning with base station to jointly mitigate the impact of device heterogeneity and transmission unreliability. Second, a tractable upper bound on the inference risk gap is derived based on theoretical analysis. To improve the generalization capability, we formulate a non-convex mixed-integer programming problem with long-term constraints, and decouple it into model switching, transmit power control, and bandwidth allocation subproblems. An online optimization algorithm is developed to solve the problems with polynomial computational complexity. Finally, the simulation results on the SST-2 and QNLI data sets demonstrate the performance gains in test accuracy and energy efficiency. Show Chinese abstract

边缘智能已成为一种有前景的策略，为移动设备提供低延迟和无处不在的服务。 基础模型微调机制的最新进展通过将低秩适应（LoRA）与联邦学习相结合，使边缘智能成为可能。 然而，在无线网络中，设备异构性和边缘设备上的资源限制对联邦微调的性能构成了重大威胁。 为了解决这些问题，我们提出通过在线学习优化异构无线网络中的联邦微调。 首先，提供了无线网络中基于切换的联邦微调框架。 边缘设备动态切换到LoRA模块，与基站联合进行联邦微调，以共同缓解设备异构性和传输不可靠的影响。 其次，基于理论分析推导了推理风险差距的可处理上界。 为了提高泛化能力，我们制定一个带有长期约束的非凸混合整数规划问题，并将其分解为模型切换、发射功率控制和带宽分配子问题。 开发了一种在线优化算法，以多项式计算复杂度解决这些问题。 最后，在SST-2和QNLI数据集上的仿真结果证明了测试准确率和能效的性能提升。

[7] arXiv:2509.19310 (cross-list from eess.SP) [cn-pdf, pdf, html, other]

Title: A Novel Two-Dimensional Wigner Distribution Framework via the Quadratic Phase Fourier Transform with a Non-Separable Kernel Show Chinese title

Title: 通过非可分离核的二次相位傅里叶变换的新型二维威格纳分布框架

Mukul Chauhan, Waseem Z. Lone, Amit K. Verma

Subjects: Signal Processing (eess.SP) ; Information Theory (cs.IT) ; Functional Analysis (math.FA)

This paper introduces a novel time-frequency distribution, referred to as the Two-Dimensional Non-Separable Quadratic Phase Wigner Distribution (2D-NSQPWD), formulated within the framework of the Two-Dimensional Non-Separable Quadratic Phase Fourier Transform (2D-NSQPFT). By replacing the classical Fourier kernel with the NSQPFT kernel, the proposed distribution generalizes the classical Wigner distribution and effectively captures complex, non-separable signal structures. We rigorously establish several key properties of the 2D-NSQPWD, including time and frequency shift invariance, marginal behavior, conjugate symmetry, convolution relations, and Moyal's identity. Furthermore, the connection between the 2D-NSQPWD and the two-dimensional short-time Fourier transform (2D-STFT) is explored. The distribution's effectiveness is demonstrated through its application to single-, bi-, and tri-component two-dimensional linear frequency modulated (2D-LFM) signals, where it shows superior performance in cross-term suppression and signal localization. Show Chinese abstract

本文介绍了一种新的时频分布，称为二维非可分二次相位Wigner分布（2D-NSQPWD），该分布是在二维非可分二次相位傅里叶变换（2D-NSQPFT）框架内提出的。 通过将经典傅里叶核替换为NSQPFT核，所提出的分布推广了经典Wigner分布，并能有效捕捉复杂的非可分信号结构。 我们严格建立了2D-NSQPWD的几个关键性质，包括时间与频率平移不变性、边缘行为、共轭对称性、卷积关系和Moyal恒等式。 此外，探讨了2D-NSQPWD与二维短时傅里叶变换（2D-STFT）之间的联系。 该分布的有效性通过其在单分量、双分量和三分量二维线性频率调制（2D-LFM）信号中的应用得到证明，显示出在交叉项抑制和信号定位方面的优越性能。

[8] arXiv:2509.19312 (cross-list from eess.SP) [cn-pdf, pdf, html, other]

Title: E2E Learning Massive MIMO for Multimodal Semantic Non-Orthogonal Transmission and Fusion Show Chinese title

Title: 端到端学习大规模MIMO用于多模态语义非正交传输与融合

Minghui Wu, Zhen Gao

Subjects: Signal Processing (eess.SP) ; Artificial Intelligence (cs.AI) ; Information Theory (cs.IT) ; Machine Learning (cs.LG)

Massive multiple-input multiple-output (MIMO) promises high spectral efficiency but also leads to high-dimensional downlink channel state information (CSI), which complicates real-time channel acquisition and precoding. To address this, we propose an end-to-end (E2E) uplink-downlink CSI fusion precoding network that jointly models downlink CSI reference signal (CSI-RS) design, CSI feedback, and base-station (BS) precoding within a single E2E neural architecture. Concretely, a projection network built on the MAXIM architecture takes uplink sounding reference signals (SRS) as input and outputs frequency-, beam-, and port-domain projection matrices for designing downlink CSI-RS. User equipment (UE) then compresses/quantizes the resulting CSI-RS observations and feeds back a compact representation. At the base station (BS), two complementary branches produce candidate precoders: one is a feedback-only precoding network driven by quantized downlink observations, and the other is an SRS-only precoding network driven by uplink SRS. These candidate precoders are subsequently combined by a fusion precoding network to yield the final transmit precoder. All the modules are trained with a spectral-efficiency-oriented loss under a three-stage schedule. Simulation results show that the proposed approach effectively harnesses both SRS-derived information and UE feedback, achieving markedly better performance than conventional baselines. Show Chinese abstract

大规模多输入多输出（MIMO）有望实现高频谱效率，但也导致了高维下行链路信道状态信息（CSI），这使得实时信道获取和预编码变得复杂。 为了解决这个问题，我们提出了一种端到端（E2E）上行链路-下行链路CSI融合预编码网络，在单一E2E神经架构中联合建模下行链路CSI参考信号（CSI-RS）设计、CSI反馈和基站（BS）预编码。 具体来说，一个基于MAXIM架构的投影网络以上行链路探测参考信号（SRS）作为输入，并输出用于设计下行链路CSI-RS的频率、波束和端口域投影矩阵。 用户设备（UE）随后对生成的CSI-RS观测值进行压缩/量化，并反馈一个紧凑表示。 在基站（BS）处，两个互补分支生成候选预编码器：一个是仅由量化下行链路观测驱动的反馈预编码网络，另一个是仅由上行链路SRS驱动的SRS预编码网络。 这些候选预编码器随后由一个融合预编码网络结合，以产生最终的发射预编码器。 所有模块在三阶段调度下使用面向频谱效率的损失函数进行训练。 仿真结果表明，所提出的方法有效利用了来自SRS的信息和UE反馈，性能明显优于传统基线方法。

[9] arXiv:2509.19340 (cross-list from eess.SP) [cn-pdf, pdf, html, other]

Title: Joint Channel Estimation and Computation Offloading in Fluid Antenna-assisted MEC Networks Show Chinese title

Title: 流体天线辅助的MEC网络中的联合信道估计与计算卸载

Ying Ju, Mingdong Li, Haoyu Wang, Lei Liu, Youyang Qu, Mianxiong Dong, Victor C. M. Leung, Chau Yuen

Subjects: Signal Processing (eess.SP) ; Artificial Intelligence (cs.AI) ; Information Theory (cs.IT) ; Networking and Internet Architecture (cs.NI)

With the emergence of fluid antenna (FA) in wireless communications, the capability to dynamically adjust port positions offers substantial benefits in spatial diversity and spectrum efficiency, which are particularly valuable for mobile edge computing (MEC) systems. Therefore, we propose an FA-assisted MEC offloading framework to minimize system delay. This framework faces two severe challenges, which are the complexity of channel estimation due to dynamic port configuration and the inherent non-convexity of the joint optimization problem. Firstly, we propose Information Bottleneck Metric-enhanced Channel Compressed Sensing (IBM-CCS), which advances FA channel estimation by integrating information relevance into the sensing process and capturing key features of FA channels effectively. Secondly, to address the non-convex and high-dimensional optimization problem in FA-assisted MEC systems, which includes FA port selection, beamforming, power control, and resource allocation, we propose a game theory-assisted Hierarchical Twin-Dueling Multi-agent Algorithm (HiTDMA) based offloading scheme, where the hierarchical structure effectively decouples and coordinates the optimization tasks between the user side and the base station side. Crucially, the game theory effectively reduces the dimensionality of power control variables, allowing deep reinforcement learning (DRL) agents to achieve improved optimization efficiency. Numerical results confirm that the proposed scheme significantly reduces system delay and enhances offloading performance, outperforming benchmarks. Additionally, the IBM-CCS channel estimation demonstrates superior accuracy and robustness under varying port densities, contributing to efficient communication under imperfect CSI. Show Chinese abstract

随着流体天线（FA）在无线通信中的出现，动态调整端口位置的能力在空间分集和频谱效率方面提供了显著的优势，这对移动边缘计算（MEC）系统尤其有价值。 因此，我们提出了一种FA辅助的MEC卸载框架，以最小化系统延迟。 该框架面临两个严峻的挑战，即由于动态端口配置导致的信道估计复杂性以及联合优化问题的固有非凸性。 首先，我们提出了信息瓶颈度量增强的信道压缩感知（IBM-CCS），通过在感知过程中整合信息相关性并有效捕捉FA信道的关键特征，从而提升FA信道估计。 其次，为了解决FA辅助MEC系统中的非凸和高维优化问题，该问题包括FA端口选择、波束成形、功率控制和资源分配，我们提出了一种基于博弈论的分层双优多智能体算法（HiTDMA）辅助的卸载方案，其中分层结构有效地解耦并协调用户侧和基站侧的优化任务。 至关重要的是，博弈论有效降低了功率控制变量的维度，使深度强化学习（DRL）代理能够实现更高效的优化。 数值结果证实，所提出的方案显著降低了系统延迟并提升了卸载性能，优于基准方案。 此外，IBM-CCS信道估计在不同端口密度下表现出更高的准确性和鲁棒性，有助于在不完美CSI条件下实现高效的通信。

[10] arXiv:2509.19342 (cross-list from eess.SP) [cn-pdf, pdf, html, other]

Title: A Measurement Report Data-Driven Framework for Localized Statistical Channel Modeling Show Chinese title

Title: 一种用于局部统计信道建模的测量报告数据驱动框架

Xinyu Qin, Ye Xue, Qi Yan, Shutao Zhang, Bingsheng Peng, Tsung-Hui Chang

Subjects: Signal Processing (eess.SP) ; Information Theory (cs.IT) ; Machine Learning (cs.LG)

Localized statistical channel modeling (LSCM) is crucial for effective performance evaluation in digital twin-assisted network optimization. Solely relying on the multi-beam reference signal receiving power (RSRP), LSCM aims to model the localized statistical propagation environment by estimating the channel angular power spectrum (APS). However, existing methods rely heavily on drive test data with high collection costs and limited spatial coverage. In this paper, we propose a measurement report (MR) data-driven framework for LSCM, exploiting the low-cost and extensive collection of MR data. The framework comprises two novel modules. The MR localization module addresses the issue of missing locations in MR data by introducing a semi-supervised method based on hypergraph neural networks, which exploits multi-modal information via distance-aware hypergraph modeling and hypergraph convolution for location extraction. To enhance the computational efficiency and solution robustness, LSCM operates at the grid level. Compared to independently constructing geographically uniform grids and estimating channel APS, the joint grid construction and channel APS estimation module enhances robustness in complex environments with spatially non-uniform data by exploiting their correlation. This module alternately optimizes grid partitioning and APS estimation using clustering and improved sparse recovery for the ill-conditioned measurement matrix and incomplete observations. Through comprehensive experiments on a real-world MR dataset, we demonstrate the superior performance and robustness of our framework in localization and channel modeling. Show Chinese abstract

局部化统计信道建模（LSCM）对于数字孪生辅助的网络优化中的有效性能评估至关重要。 仅依赖多波束参考信号接收功率（RSRP），LSCM旨在通过估计信道角度功率谱（APS）来建模局部化的统计传播环境。 然而，现有方法严重依赖于成本高且空间覆盖有限的路测数据。 在本文中，我们提出了一种基于测量报告（MR）数据的框架用于LSCM，利用了MR数据低成本和广泛收集的特点。 该框架包含两个新模块。 MR定位模块通过引入基于超图神经网络的半监督方法，解决了MR数据中缺失位置的问题，该方法通过距离感知的超图建模和超图卷积来利用多模态信息进行位置提取。 为了提高计算效率和解决方案的鲁棒性，LSCM在网格级别运行。 与独立构建地理均匀网格并估计信道APS相比，联合网格构建和信道APS估计模块通过利用它们的相关性，在具有空间非均匀数据的复杂环境中增强了鲁棒性。 该模块通过聚类和改进的稀疏恢复来交替优化网格划分和APS估计，针对病态测量矩阵和不完整观测。 通过在真实世界MR数据集上的全面实验，我们证明了我们的框架在定位和信道建模方面的优越性能和鲁棒性。

[11] arXiv:2509.19382 (cross-list from eess.SP) [cn-pdf, pdf, html, other]

Title: Neural Network Based Framework for Passive Intermodulation Cancellation in MIMO Systems Show Chinese title

Title: 基于神经网络的MIMO系统中无源互调干扰消除框架

Xiaolong Li, Zhi-qin John Xu, Peiting You, Yifei Zhu

Subjects: Signal Processing (eess.SP) ; Information Theory (cs.IT) ; Machine Learning (cs.LG)

Passive intermodulation (PIM) has emerged as a critical source of self-interference in modern MIMO-OFDM systems, especially under the stringent requirements of 5G and beyond. Conventional cancellation methods often rely on complex nonlinear models with limited scalability and high computational cost. In this work, we propose a lightweight deep learning framework for PIM cancellation that leverages depthwise separable convolutions and dilated convolutions to efficiently capture nonlinear dependencies across antennas and subcarriers. To further enhance convergence, we adopt a cyclic learning rate schedule and gradient clipping. In a controlled MIMO experimental setup, the method effectively suppresses third-order passive intermodulation (PIM) distortion, achieving up to 29dB of average power error (APE) with only 11k trainable parameters. These results highlight the potential of compact neural architectures for scalable interference mitigation in future wireless communication systems. Show Chinese abstract

无源互调（PIM）已成为现代MIMO-OFDM系统中自干扰的关键来源，尤其是在5G及更高要求的严格条件下。传统的消除方法通常依赖于复杂的非线性模型，具有有限的可扩展性和高计算成本。在本工作中，我们提出了一种轻量级的深度学习框架用于PIM消除，该框架利用深度可分离卷积和扩张卷积来高效捕捉天线和子载波之间的非线性依赖关系。为了进一步提高收敛性，我们采用了循环学习率调度和梯度裁剪。在一个受控的MIMO实验设置中，该方法有效抑制了三阶无源互调（PIM）失真，仅使用11k个可训练参数就实现了高达29dB的平均功率误差（APE）。这些结果突显了紧凑神经架构在未来的无线通信系统中可扩展干扰缓解方面的潜力。

[12] arXiv:2509.19383 (cross-list from eess.SP) [cn-pdf, pdf, html, other]

Title: Impact of RHIs and ipSIC on Active RIS-NOMA Systems with Low-Precision ADCs Show Chinese title

Title: RHIs和ipSIC对低精度ADC主动RIS-NOMA系统的影响

Qianqian Li, Hua Li, Shiya Hao, Lintao Li, Xiaoming Dai

Subjects: Signal Processing (eess.SP) ; Information Theory (cs.IT) ; Performance (cs.PF)

This study evaluates the performance of an active reconfigurable intelligent surface (ARIS)-assisted non-orthogonal multiple access (NOMA) system employing low-precision analog-to-digital converters (ADCs). Analytical approximations for the outage probability (OP) are derived, considering residual hardware impairments (RHIs) and imperfect successive interference cancellation (ipSIC). Additionally, we analyze the asymptotic OP, system throughput, and diversity order at high signal-to-noise ratios (SNRs). Simulation results demonstrate that the proposed quantized ARIS-NOMA system outperforms its passive counterpart (PRIS-NOMA), achieving lower OP and higher throughput with reduced transmit power requirements and fewer reflecting elements. Moreover, the outage performance of both quantized ARIS-NOMA and PRIS-NOMA systems demonstrates significant improvement as the number of reflecting elements increases. The negative impacts of low-precision ADCs can be effectively mitigated by optimizing transmit power and scaling the number of reflecting elements. Show Chinese abstract

本研究评估了采用低精度模数转换器(ADCs)的主动可重构智能表面(ARIS)辅助非正交多址接入(NOMA)系统的性能。 考虑残余硬件损伤(RHIs)和不完全的连续干扰消除(ipSIC)，推导了中断概率(OP)的分析近似值。 此外，我们分析了在高信噪比(SNRs)下的渐近OP、系统吞吐量和分集阶数。 仿真结果表明，所提出的量化ARIS-NOMA系统优于其被动对应系统(PRIS-NOMA)，在减少发射功率需求和反射元件数量的同时，实现了更低的OP和更高的吞吐量。 此外，随着反射元件数量的增加，量化ARIS-NOMA和PRIS-NOMA系统的中断性能均表现出显著改善。 通过优化发射功率并调整反射元件的数量，可以有效缓解低精度ADCs的负面影响。

[13] arXiv:2509.19491 (cross-list from quant-ph) [cn-pdf, pdf, html, other]

Title: Martingale Projections and Quantum Decoherence Show Chinese title

Title: 鞅投影与量子退相干

Lane P. Hughston, Levent A. Mengütürk

Comments: 17 pages

Subjects: Quantum Physics (quant-ph) ; Information Theory (cs.IT) ; Probability (math.PR)

We introduce so-called super/sub-martingale projections as a family of endomorphisms defined on unions of Polish spaces. Such projections allow us to identify martingales as collections of transformations that relate path-valued random variables to each other under conditional expectations. In this sense, super/sub-martingale projections are random functionals that (i) are boundedness preserving and (ii) satisfy a conditional expectation criterion similar to that of the classical martingale theory. As an application to the theory of open quantum systems, we prove (a) that any system-environment interaction that manifests a supermartingale projection on the density matrix gives rise to decoherence, and (b) that any system-environment interaction that manifests a submartingale projection gives rise an increase in Shannon-Wiener information. It follows (c) that martingale projections in an open quantum system give rise both to quantum decoherence and to information gain. Show Chinese abstract

我们引入所谓的超/次鞅投影，作为定义在波兰空间并集上的自同态族。 这些投影使我们能够将鞅识别为在条件期望下将路径值随机变量相互关联的变换集合。 从这个意义上说，超/次鞅投影是随机泛函，(i) 保持有界性，并且 (ii) 满足类似于经典鞅理论中的条件期望准则。 作为开放量子系统理论的应用，我们证明 (a) 任何在密度矩阵上表现出超鞅投影的系统-环境相互作用会导致退相干，以及 (b) 任何在密度矩阵上表现出次鞅投影的系统-环境相互作用会导致香农-维纳信息的增加。 由此得出 (c) 在开放量子系统中，鞅投影同时导致量子退相干和信息增益。

[14] arXiv:2509.20101 (cross-list from stat.ML) [cn-pdf, pdf, html, other]

Title: First-Extinction Law for Resampling Processes Show Chinese title

Title: 重采样过程的第一灭绝定律

Matteo Benati, Alessandro Londei, Denise Lanzieri, Vittorio Loreto

Subjects: Machine Learning (stat.ML) ; Information Theory (cs.IT) ; Machine Learning (cs.LG) ; Statistics Theory (math.ST) ; Data Analysis, Statistics and Probability (physics.data-an) ; Populations and Evolution (q-bio.PE)

Extinction times in resampling processes are fundamental yet often intractable, as previous formulas scale as $2^M$ with the number of states $M$ present in the initial probability distribution. We solve this by treating multinomial updates as independent square-root diffusions of zero drift, yielding a closed-form law for the first-extinction time. We prove that the mean coincides exactly with the Wright-Fisher result of Baxter et al., thereby replacing exponential-cost evaluations with a linear-cost expression, and we validate this result through extensive simulations. Finally, we demonstrate predictive power for model collapse in a simple self-training setup: the onset of collapse coincides with the resampling-driven first-extinction time computed from the model's initial stationary distribution. These results hint to a unified view of resampling extinction dynamics. Show Chinese abstract

在重采样过程中，灭绝时间是基本但常常难以处理的，因为之前的公式随着初始概率分布中状态数$M$的增加而按$2^M$的比例增长。 我们通过将多项式更新视为零漂移的平方根扩散来解决这个问题，从而得到了首次灭绝时间的显式公式。 我们证明了平均值恰好与 Baxter 等人的 Wright-Fisher 结果一致，从而用线性成本表达式取代了指数成本计算，并通过大量模拟验证了这一结果。 最后，我们在一个简单的自训练设置中展示了对模型崩溃的预测能力：崩溃的发生与从模型初始平稳分布计算出的重采样驱动的首次灭绝时间一致。 这些结果暗示了重采样灭绝动力学的统一视角。

Replacement submissions (showing 7 of 7 entries )

[15] arXiv:1701.06545 (replaced) [cn-pdf, pdf, html, other]

Title: Exponent Function for Stationary Memoryless Channels with Input Cost at Rates above the Capacity Show Chinese title

Title: 平稳无记忆信道的指数函数，输入代价在容量以上的速率

Yasutada Oohama

Comments: 20pages. arXiv admin note: text overlap with arXiv:1701.06357

Subjects: Information Theory (cs.IT)

We consider the stationaly memoryless channels with input cost. We prove that for transmission rates above the capacity the correct probability of decoding tends to zero exponentially as the block length $n$ of codes tends to infinity. In the case where both of channel input and output sets are finite, we determine the optimal exponent function on the above exponential decay of the correct probability. To derive this result we use a new technique called the recuresive method, which is based on the information spectrum approach. The recursive method utilize a certain recursive structure on the information spectrum quantities. Show Chinese abstract

我们考虑具有输入代价的平稳无记忆信道。 我们证明，当传输速率高于容量时，解码的正确概率随着码长$n$趋向于无穷大而指数趋向于零。 在信道输入和输出集合都是有限的情况下，我们确定了上述正确概率指数衰减的最佳指数函数。 为了得到这个结果，我们使用了一种称为递归方法的新技术，该方法基于信息谱方法。 递归方法利用信息谱量上的某种递归结构。

[16] arXiv:2401.15722 (replaced) [cn-pdf, pdf, other]

Title: A Combinatorial Perspective on Random Access Efficiency for DNA Storage Show Chinese title

Title: 随机存取效率的组合视角用于DNA存储

Anina Gruica, Daniella Bar-Lev, Alberto Ravagnani, Eitan Yaakobi

Subjects: Information Theory (cs.IT) ; Combinatorics (math.CO)

We investigate the fundamental limits of the recently proposed random access coverage depth problem for DNA data storage. Under this paradigm, it is assumed that the user information consists of $k$ information strands, which are encoded into $n$ strands via a generator matrix $G$. During the sequencing process, the strands are read uniformly at random, as each strand is available in a large number of copies. In this context, the random access coverage depth problem refers to the expected number of reads (i.e., sequenced strands) required to decode a specific information strand requested by the user. This problem heavily depends on the generator matrix $G$, and besides computing the expectation for different choices of $G$, the goal is to construct matrices that minimize the maximum expectation over all possible requested information strands, denoted by $T_{\max}(G)$. In this paper, we introduce new techniques to investigate the random access coverage depth problem, capturing its combinatorial nature and identifying the structural properties of generator matrices that are advantageous. We establish two general formulas to determine $T_{\max}(G)$ for arbitrary generator matrices. The first formula depends on the linear dependencies between columns of $G$, whereas the second formula takes into account recovery sets and their intersection structure. We also introduce the concept of recovery balanced codes and provide three sufficient conditions for a code to be recovery balanced. These conditions can be used to compute $T_{\max}(G)$ for various families of codes, such as MDS, simplex, Hamming, and binary Reed-Muller codes. Additionally, we study the performance of modified systematic MDS and simplex matrices, showing that the best results for $T_{\max}(G)$ are achieved with a specific combination of encoded strands and replication of the information strands. Show Chinese abstract

我们研究了最近提出的DNA数据存储中的随机访问覆盖深度问题的基本极限。 在此范式下，假设用户信息由$k$条信息链组成，这些链通过生成矩阵$G$编码为$n$条链。 在测序过程中，链是均匀随机读取的，因为每条链都有大量副本可用。 在此背景下，随机访问覆盖深度问题指的是解码用户请求的特定信息链所需的平均读取次数（即测序链的数量）。 这个问题高度依赖于生成矩阵$G$，除了计算不同选择的$G$的期望值外，目标是构造使所有可能请求的信息链的最大期望值最小化的矩阵，记为$T_{\max}(G)$。 在本文中，我们引入了新的技术来研究随机访问覆盖深度问题，捕捉其组合性质，并确定具有优势的生成矩阵的结构特性。 我们建立了两个通用公式，以确定任意生成矩阵的$T_{\max}(G)$。 第一个公式依赖于$G$列之间的线性相关性，而第二个公式考虑了恢复集及其交集结构。 我们还引入了恢复平衡码的概念，并提供了代码成为恢复平衡的三个充分条件。 这些条件可用于计算各种码族的$T_{\max}(G)$，例如 MDS、单纯、汉明和二元 Reed-Muller 码。 此外，我们研究了修改后的系统 MDS 和单极矩阵的性能，表明通过编码链和信息链的特定组合可以获得$T_{\max}(G)$的最佳结果。

[17] arXiv:2411.02225 (replaced) [cn-pdf, pdf, html, other]

Title: Sparse Max-Affine Regression Show Chinese title

Title: 稀疏最大仿射回归

Haitham Kanj, Seonho Kim, Kiryung Lee

Subjects: Machine Learning (stat.ML) ; Information Theory (cs.IT) ; Machine Learning (cs.LG) ; Statistics Theory (math.ST)

This paper presents Sparse Gradient Descent as a solution for variable selection in convex piecewise linear regression, where the model is given as the maximum of $k$-affine functions $ x \mapsto \max_{j \in [k]} \langle a_j^\star, x \rangle + b_j^\star$ for $j = 1,\dots,k$. Here, $\{ a_j^\star\}_{j=1}^k$ and $\{b_j^\star\}_{j=1}^k$ denote the ground-truth weight vectors and intercepts. A non-asymptotic local convergence analysis is provided for Sp-GD under sub-Gaussian noise when the covariate distribution satisfies the sub-Gaussianity and anti-concentration properties. When the model order and parameters are fixed, Sp-GD provides an $\epsilon$-accurate estimate given $\mathcal{O}(\max(\epsilon^{-2}\sigma_z^2,1)s\log(d/s))$ observations where $\sigma_z^2$ denotes the noise variance. This also implies the exact parameter recovery by Sp-GD from $\mathcal{O}(s\log(d/s))$ noise-free observations. The proposed initialization scheme uses sparse principal component analysis to estimate the subspace spanned by $\{ a_j^\star\}_{j=1}^k$, then applies an $r$-covering search to estimate the model parameters. A non-asymptotic analysis is presented for this initialization scheme when the covariates and noise samples follow Gaussian distributions. When the model order and parameters are fixed, this initialization scheme provides an $\epsilon$-accurate estimate given $\mathcal{O}(\epsilon^{-2}\max(\sigma_z^4,\sigma_z^2,1)s^2\log^4(d))$ observations. A new transformation named Real Maslov Dequantization (RMD) is proposed to transform sparse generalized polynomials into sparse max-affine models. The error decay rate of RMD is shown to be exponentially small in its temperature parameter. Furthermore, theoretical guarantees for Sp-GD are extended to the bounded noise model induced by RMD. Numerical Monte Carlo results corroborate theoretical findings for Sp-GD and the initialization scheme. Show Chinese abstract

本文提出了稀疏梯度下降方法，用于凸分段线性回归中的变量选择，其中模型为$k$-仿射函数$ x \mapsto \max_{j \in [k]} \langle a_j^\star, x \rangle + b_j^\star$的最大值，对于$j = 1,\dots,k$。 此处，$\{ a_j^\star\}_{j=1}^k$和$\{b_j^\star\}_{j=1}^k$表示真实权重向量和截距。 当协变量分布满足次高斯性和反集中性质时，在次高斯噪声下为 Sp-GD 提供了非渐近局部收敛分析。 当模型阶数和参数固定时，Sp-GD在给定$\mathcal{O}(\max(\epsilon^{-2}\sigma_z^2,1)s\log(d/s))$个观测值的情况下提供一个$\epsilon$-准确的估计，其中$\sigma_z^2$表示噪声方差。这也意味着Sp-GD可以从$\mathcal{O}(s\log(d/s))$个无噪声观测值中精确恢复参数。所提出的初始化方案使用稀疏主成分分析来估计由$\{ a_j^\star\}_{j=1}^k$张成的子空间，然后应用一个$r$-覆盖搜索来估计模型参数。当协变量和噪声样本服从高斯分布时，对该初始化方案进行了非渐近分析。 当模型阶数和参数固定时，该初始化方案在给定$\mathcal{O}(\epsilon^{-2}\max(\sigma_z^4,\sigma_z^2,1)s^2\log^4(d))$个观测值的情况下提供$\epsilon$-准确的估计。 一种名为实Maslov去量化（RMD）的新变换被提出，用于将稀疏广义多项式转换为稀疏最大仿射模型。 RMD 的误差衰减率被证明在其温度参数上呈指数级小。 此外，Sp-GD 的理论保证被扩展到由 RMD 引入的有界噪声模型。 数值蒙特卡罗结果验证了 Sp-GD 和初始化方案的理论结果。

[18] arXiv:2502.05935 (replaced) [cn-pdf, pdf, html, other]

Title: Interactive Inference: A Neuromorphic Theory of Human-Computer Interaction Show Chinese title

Title: 交互推理：人机交互的神经形态理论

Roel Vertegaal, Timothy Merritt, Saul Greenberg, Aneesh P. Tarun, Zhen Li, Zafeirios Fountas

Comments: 18 pages, 7 figures, 1 table, 37 mathematical formulas, in press

Subjects: Human-Computer Interaction (cs.HC) ; Information Theory (cs.IT)

Neuromorphic Human-Computer Interaction (HCI) is a theoretical approach to designing better user experiences (UX) motivated by advances in the understanding of the neurophysiology of the brain. Inspired by the neuroscientific theory of Active Inference, Interactive Inference is a first example of such approach. It offers a simplified interpretation of Active Inference that allows designers to more readily apply this theory to design and evaluation. In Interactive Inference, user behaviour is modeled as Bayesian inference on progress and goal distributions that predicts the next action. We show how the error between goal and progress distributions, or Bayesian surprise, can be modeled as a simple mean square error of the signal-to-noise ratio (SNR) of a task. The problem is that the user's capacity to process Bayesian surprise follows the logarithm of this SNR. This means errors rise quickly once average capacity is exceeded. Our model allows the quantitative analysis of performance and error using one framework that can provide real-time estimates of the mental load in users that needs to be minimized by design. We show how three basic laws of HCI, Hick's Law, Fitts' Law and the Power Law can be expressed using our model. We then test the validity of the model by empirically measuring how well it predicts human performance and error in a car following task. Results suggest that driver processing capacity indeed is a logarithmic function of the SNR of the distance to a lead car. This result provides initial evidence that Interactive Interference can be useful as a new theoretical design tool. Show Chinese abstract

神经形态人机交互（HCI）是一种理论方法，旨在通过大脑神经生理学理解的进展来设计更好的用户体验（UX）。 受主动推断的神经科学理论启发，交互推断是这种方法的第一个例子。 它提供了一种简化的主动推断解释，使设计师能够更方便地将这一理论应用于设计和评估。 在交互推断中，用户行为被建模为对进展和目标分布的贝叶斯推断，用于预测下一步行动。 我们展示了目标分布与进展分布之间的误差，或贝叶斯意外，可以建模为任务信噪比（SNR）的简单均方误差。 问题是用户的处理贝叶斯意外的能力遵循该SNR的对数。 这意味着一旦平均能力被超越，错误就会迅速增加。 我们的模型允许使用一个框架对性能和错误进行定量分析，该框架可以实时估计用户的心理负荷，设计需要最小化这种负荷。 我们展示了三个基本的人机交互定律，即 Hick's Law、Fitts' Law 和 Power Law 可以用我们的模型来表示。 然后我们通过实证测量来测试模型的有效性，即它在汽车跟随任务中预测人类表现和错误的能力。 结果表明，驾驶员的处理能力确实是与前车距离的 SNR 的对数函数。 这一结果提供了初步证据，表明交互推断可以作为新的理论设计工具发挥作用。

[19] arXiv:2502.15565 (replaced) [cn-pdf, pdf, html, other]

Title: Benefits of Mutual Coupling in Dynamic Metasurface Antennas Show Chinese title

Title: 动态超表面天线中互耦的优势

Hugo Prod'homme, Jean Tapie, Luc Le Magoarou, Philipp del Hougne

Comments: 15 pages, 8 figures, submitted to an IEEE Journal

Subjects: Applied Physics (physics.app-ph) ; Information Theory (cs.IT) ; Signal Processing (eess.SP)

Dynamic metasurface antennas (DMAs) are a promising embodiment of next-generation reconfigurable antenna technology to realize base stations and access points with reduced cost and power consumption. A DMA is a thin structure patterned on its front with reconfigurable radiating metamaterial elements (meta-atoms) that are excited by waveguides or cavities. Mutual coupling between the meta-atoms can result in a strongly non-linear dependence of the DMA's radiation pattern on the configuration of its meta-atoms. However, besides the obvious algorithmic challenges of working with physics-compliant DMA models, it remains unclear how mutual coupling in DMAs influences the ability to achieve a desired wireless functionality. In this paper, we provide theoretical, numerical and experimental evidence that strong mutual coupling in DMAs increases the radiation pattern sensitivity to the DMA configuration and thereby boosts the available control over the radiation pattern, improving the ability to tailor the radiation pattern to the requirements of a desired wireless functionality. Counterintuitively, we hence encourage next-generation DMA implementations to enhance (rather than suppress) mutual coupling, in combination with suitable physics-compliant modeling and optimization. We expect the unveiled mechanism by which mutual coupling boosts the radiation pattern control to also apply to other reconfigurable antenna systems based on tunable lumped elements. Show Chinese abstract

动态超表面天线（DMAs）是下一代可重构天线技术的一种有前景的实现方式，旨在实现成本和功耗更低的基站和接入点。 DMA 是一种在其前面带有可重构辐射超材料元件（元原子）的薄结构，这些元原子由波导或腔体激发。 元原子之间的互耦可能导致 DMA 的辐射图样对其元原子配置产生强烈的非线性依赖。 然而，除了在使用符合物理规律的 DMA 模型时明显的算法挑战外，目前尚不清楚 DMA 中的互耦如何影响实现所需无线功能的能力。 在本文中，我们提供了理论、数值和实验证据，表明 DMA 中的强互耦增加了辐射图样对 DMA 配置的敏感性，从而提高了对辐射图样的可用控制能力，改善了将辐射图样定制为所需无线功能要求的能力。 出乎意料的是，因此我们鼓励下一代 DMA 实现增强（而不是抑制）互耦，同时结合适当的符合物理规律的建模和优化。 我们预计通过互耦增强辐射图样控制的未揭示机制也适用于基于可调集中参数元件的其他可重构天线系统。

[20] arXiv:2507.04284 (replaced) [cn-pdf, pdf, html, other]

Title: High-Availability Integrity Monitoring for Multi-Constellation GNSS Navigation with Non-Gaussian Errors Show Chinese title

Title: 多星座GNSS导航中具有非高斯误差的高可用性完整性监测

Penggao Yan, Ronghe Jin, Junyi Zhang, Cheng-Wei Wang, Li-Ta Hsu

Comments: Submitted to Aerospace Systems

Subjects: Signal Processing (eess.SP) ; Information Theory (cs.IT)

Global navigation satellite systems (GNSS) are essential for aviation, requiring strict integrity monitoring to alert users to hazardously misleading information. Conventional receiver autonomous integrity monitoring (RAIM) and advanced RAIM (ARAIM) rely heavily on Gaussian models in bounding nominal errors, which can be overly conservative with real-world non-Gaussian errors with heavy tails, such as the satellite clock and orbit errors. This paper proposes an extended jackknife detector capable of detecting multiple simultaneous faults with non-Gaussian nominal errors. Furthermore, an integrity monitoring algorithm, jackknife ARAIM, is developed by systematically exploiting the properties of the jackknife detector in the range domain. A tight bound of the integrity risk is derived by quantifying the impacts of hypothetical fault vectors on the position solution. The proposed method is examined in worldwide simulations, with the nominal measurement error simulated based on authentic experimental data, which reveals different findings in existing research. In a setting of a single Global Positioning System (GPS) constellation, the proposed method reduces the 99.5 percentile vertical protection level (VPL) 45m, where the VPL of the baseline ARAIM is larger than 50m in most user locations. For dual-constellation (GPS-Galileo) settings, baseline ARAIM suffers VPL inflation over 60m due to the over-conservatism induced by the heavy-tailed Galileo signal-in-space range errors, whereas the proposed jackknife ARAIM retains VPL below 40m, achieving over 92% normal operations for a 35m Vertical Alert Limit. These improvements have promising potential to support localizer performance with vertical guidance (LPV) with a decision height of 200 ft, enhancing integrity and availability for multi-constellation GNSS applications. Show Chinese abstract

全球导航卫星系统（GNSS）对于航空至关重要，需要严格的完整性监控以提醒用户注意危险性误导信息。传统的接收机自主完整性监控（RAIM）和高级RAIM（ARAIM）在界定正常误差时严重依赖高斯模型，这在具有重尾的实际非高斯误差（如卫星钟和轨道误差）情况下可能过于保守。本文提出了一种扩展的jackknife检测器，能够检测具有非高斯正常误差的多个同时故障。此外，通过系统地利用范围域中jackknife检测器的特性，开发了一种完整性监控算法，即jackknife ARAIM。通过量化假设故障向量对位置解的影响，推导出了完整性风险的紧致界限。所提出的方法在全世界的仿真中进行了检验，正常测量误差是基于真实实验数据模拟的，这揭示了现有研究中的不同发现。在一个单一的全球定位系统（GPS）星座设置中，所提出的方法将99.5百分位垂直保护级别（VPL）降低了45米，而基准ARAIM的VPL在大多数用户位置都大于50米。对于双星座（GPS-Galileo）设置，基准ARAIM由于空间信号范围误差的重尾特性导致VPL膨胀超过60米，而所提出的jackknife ARAIM保持VPL低于40米，在35米垂直警报限制下实现了超过92%的正常运行。这些改进有望支持具有200英尺决断高度的局部器性能垂直引导（LPV），增强多星座GNSS应用的完整性和可用性。

[21] arXiv:2507.06232 (replaced) [cn-pdf, pdf, other]

Title: Error Exponents for Quantum Packing Problems via An Operator Layer Cake Theorem Show Chinese title

Title: 量子打包问题的误差指数通过算子层蛋糕定理

Hao-Chung Cheng, Po-Chieh Liu

Comments: v3: new added {\S}3.1: Extension to Infinite Dimensions; v2: tables and references added

Subjects: Quantum Physics (quant-ph) ; Information Theory (cs.IT) ; Mathematical Physics (math-ph) ; Functional Analysis (math.FA)

In this work, we prove a one-shot random coding bound for classical-quantum channel coding, a problem conjectured by Burnashev and Holevo in 1998. By choosing the optimal input distribution, the bound implies the optimal error exponent (i.e., the reliability function) of classical-quantum channels for rates above the critical rate, even in infinite-dimensional Hilbert spaces. Our result extends to various quantum packing-type problems, including classical communication over any fully quantum channel with or without entanglement-assistance, constant composition codes, and classical data compression with quantum side information via fixed-length or variable-length coding. Our technical ingredient is to establish an operator layer cake theorem - the directional derivative of an operator logarithm admits an integral representation of certain projections. This shows that a kind of pretty-good measurement is equivalent to a randomized Holevo-Helstrom measurement, which provides an operational explanation of why the pretty-good measurement is pretty good. Show Chinese abstract

在本工作中，我们证明了经典-量子信道编码的一次性随机编码界限，这是一个Burnashev和Holevo在1998年提出的猜想。 通过选择最优输入分布，该界限表明对于高于临界率的速率，经典-量子信道的最优错误指数（即可靠性函数）成立，即使在无限维希尔伯特空间中也是如此。 我们的结果扩展到各种量子打包型问题，包括任何完全量子信道上的经典通信（有或没有纠缠辅助），常数组成码，以及通过固定长度或可变长度编码的经典数据压缩与量子侧信息。 我们的技术要素是建立一个算子层蛋糕定理——算子对数的方向导数可以表示为某些投影的积分。 这表明一种很好的测量等价于随机化的Holevo-Helstrom测量，这提供了一个操作性解释，说明为什么很好的测量是很好的。