Physical Communication最新文献

英文中文

A complex-valued neural network approach to passive intermodulation suppression 无源互调抑制的复值神经网络方法

IF 2.2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication

Pub Date : 2026-03-01 Epub Date: 2026-02-20 DOI: 10.1016/j.phycom.2026.103050

Susong Yang , Houjun Wang , Shui Yu , Jintao Li

Artificial neural networks have recently emerged as a promising tool for digital suppression of passive intermodulation, yet most studies remain restricted to a small number of transceiver chains and do not address realistic multi-channel deployments. This paper proposes a neural PIM suppression framework for multi-carrier and multi-channel transceivers and studies multilayer perceptron (MLP) and Kolmogorov–Arnold network (KAN) architectures within a compact three-layer model. To balance the limited flexibility of standard MLPs with the computational overhead of KANs, we introduce a streamlined KAN design called SKAN by pruning the edge function to keep only the trainable spline basis expansion. We further tailor SKAN to complex-valued baseband signals through an amplitude-phase structure that preserves phase while applying the nonlinear mapping to the amplitude, which improves feature extraction efficiency and reduces inference cost. We validate the proposed approach on a commercial mobile base station equipped with eight transceiver channels under dual carrier operation. Across this setup, SKAN achieves stronger PIM suppression and faster convergence with fewer trainable parameters and fewer floating-point operations than neural baselines, indicating that it is an effective and scalable solution for practical multi-channel PIM mitigation.

人工神经网络最近成为一种很有前途的无源互调数字抑制工具，但大多数研究仍然局限于少数收发器链，并且没有解决实际的多通道部署。本文提出了一种用于多载波多通道收发器的神经PIM抑制框架，并在一个紧凑的三层模型中研究了多层感知器（MLP）和Kolmogorov-Arnold网络（KAN）结构。为了平衡标准mlp的有限灵活性和KAN的计算开销，我们引入了一种称为SKAN的流线型KAN设计，通过修剪边缘函数来只保留可训练样条基的扩展。我们进一步将SKAN定制为复杂值基带信号，通过幅度相位结构保留相位，同时对幅度进行非线性映射，从而提高特征提取效率并降低推理成本。我们在双载波操作下，在配备八个收发信道的商用移动基站上验证了所提出的方法。在此设置中，SKAN实现了比神经基线更强的PIM抑制和更快的收敛，可训练参数更少，浮点操作更少，这表明它是一种有效的可扩展的多通道PIM缓解解决方案。

{"title":"A complex-valued neural network approach to passive intermodulation suppression","authors":"Susong Yang , Houjun Wang , Shui Yu , Jintao Li","doi":"10.1016/j.phycom.2026.103050","DOIUrl":"10.1016/j.phycom.2026.103050","url":null,"abstract":"<div><div>Artificial neural networks have recently emerged as a promising tool for digital suppression of passive intermodulation, yet most studies remain restricted to a small number of transceiver chains and do not address realistic multi-channel deployments. This paper proposes a neural PIM suppression framework for multi-carrier and multi-channel transceivers and studies multilayer perceptron (MLP) and Kolmogorov–Arnold network (KAN) architectures within a compact three-layer model. To balance the limited flexibility of standard MLPs with the computational overhead of KANs, we introduce a streamlined KAN design called SKAN by pruning the edge function to keep only the trainable spline basis expansion. We further tailor SKAN to complex-valued baseband signals through an amplitude-phase structure that preserves phase while applying the nonlinear mapping to the amplitude, which improves feature extraction efficiency and reduces inference cost. We validate the proposed approach on a commercial mobile base station equipped with eight transceiver channels under dual carrier operation. Across this setup, SKAN achieves stronger PIM suppression and faster convergence with fewer trainable parameters and fewer floating-point operations than neural baselines, indicating that it is an effective and scalable solution for practical multi-channel PIM mitigation.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 103050"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147397584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A comprehensive systematic literature review on security and authentication techniques for wireless body area network (WBAN) 无线体域网络（WBAN）安全与认证技术的文献综述

IF 2.2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication

Pub Date : 2026-03-01 Epub Date: 2026-02-05 DOI: 10.1016/j.phycom.2026.103038

Navjot Kaur Sekhon , Navneet Kaur

Wireless Body Area Network (WBAN) have emerged as a transformative technology in healthcare and wellness monitoring, enabling real-time data collection, remote patient observation, and early disease detection. Numerous studies have explored WBAN architectures, security protocols, and authentication mechanisms, yet their findings remain fragmented across different applications and standards. This work presents a comprehensive systematic literature review focusing on security and authentication techniques in WBAN, evaluating their strengths, limitations, and technology readiness levels. Despite significant progress, a lack of unified, lightweight, and energy-efficient security solutions remains, which fail to address interoperability, device constraints, and evolving cyber threats in real-world healthcare deployments. Our review consolidates findings from 129 research papers (2013–2025) to develop a taxonomy of WBAN security and authentication techniques, highlighting key research trends. We adopted a systematic approach, screening articles from IEEE Xplore, ScienceDirect, ACM Digital Library, and other repositories using defined inclusion/exclusion criteria and Technology Readiness Level (TRL) based evaluation. The study categorises contributions based on areas of specialisation (e.g., clinical care, fitness, IoT integration) and employs thematic analysis to classify techniques as per their TRL levels. The review identifies critical issues like Confidentiality, Integrity, Availability (CIA), and a taxonomy of security authentication techniques with their comparative analysis.

无线体域网络（WBAN）已成为医疗保健和健康监测领域的变革性技术，可实现实时数据收集、远程患者观察和早期疾病检测。许多研究已经探索了WBAN体系结构、安全协议和身份验证机制，但是他们的发现仍然分散在不同的应用程序和标准中。本文对WBAN中的安全和认证技术进行了全面系统的文献综述，评估了它们的优势、局限性和技术准备水平。尽管取得了重大进展，但仍然缺乏统一、轻量级和节能的安全解决方案，无法解决实际医疗保健部署中的互操作性、设备限制和不断发展的网络威胁。我们的综述整合了129篇研究论文（2013-2025）的研究结果，以开发WBAN安全和认证技术的分类，突出了关键的研究趋势。我们采用了一种系统的方法，使用定义的纳入/排除标准和基于技术准备水平（TRL）的评估，筛选来自IEEE explore、ScienceDirect、ACM数字图书馆和其他存储库的文章。该研究根据专业领域（如临床护理、健身、物联网集成）对贡献进行分类，并采用主题分析根据其TRL水平对技术进行分类。该审查通过比较分析确定了诸如机密性、完整性和可用性（CIA）等关键问题，以及安全身份验证技术的分类。

{"title":"A comprehensive systematic literature review on security and authentication techniques for wireless body area network (WBAN)","authors":"Navjot Kaur Sekhon , Navneet Kaur","doi":"10.1016/j.phycom.2026.103038","DOIUrl":"10.1016/j.phycom.2026.103038","url":null,"abstract":"<div><div>Wireless Body Area Network (WBAN) have emerged as a transformative technology in healthcare and wellness monitoring, enabling real-time data collection, remote patient observation, and early disease detection. Numerous studies have explored WBAN architectures, security protocols, and authentication mechanisms, yet their findings remain fragmented across different applications and standards. This work presents a comprehensive systematic literature review focusing on security and authentication techniques in WBAN, evaluating their strengths, limitations, and technology readiness levels. Despite significant progress, a lack of unified, lightweight, and energy-efficient security solutions remains, which fail to address interoperability, device constraints, and evolving cyber threats in real-world healthcare deployments. Our review consolidates findings from 129 research papers (2013–2025) to develop a taxonomy of WBAN security and authentication techniques, highlighting key research trends. We adopted a systematic approach, screening articles from IEEE Xplore, ScienceDirect, ACM Digital Library, and other repositories using defined inclusion/exclusion criteria and Technology Readiness Level (TRL) based evaluation. The study categorises contributions based on areas of specialisation (e.g., clinical care, fitness, IoT integration) and employs thematic analysis to classify techniques as per their TRL levels. The review identifies critical issues like Confidentiality, Integrity, Availability (CIA), and a taxonomy of security authentication techniques with their comparative analysis.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 103038"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147397585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

HRVM-UNet: Dual-path vision mamba U-Net with frequency-aware skip fusion for high-resolution remote sensing semantic segmentation HRVM-UNet：用于高分辨率遥感语义分割的频率感知跳跃融合双路径视觉曼巴U-Net

IF 2.2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication

Pub Date : 2026-03-01 Epub Date: 2026-02-01 DOI: 10.1016/j.phycom.2026.103021

Tao Liu, Xinpei Wang, Yuxuan Deng

High-resolution remote sensing semantic segmentation requires simultaneously modeling long-range spatial dependencies and preserving fine-grained boundaries. Convolutional networks are efficient but often struggle to capture global context, whereas Transformers incur quadratic self-attention cost on large images. To address these issues, we propose HRVM-UNet, an asymmetric encoder–decoder segmentation framework built upon Vision Mamba (VMamba). HRVM-UNet introduces (i) a dual-path HR-VSS block that couples a selective-scan state-space global path with a multi-scale dilated-convolution local path, enabling complementary global–local representation learning; and (ii) a Frequency-Aware Skip Fusion (FASF) module that formulates skip integration as spatial–frequency coupling: CARAFE-style content-adaptive upsampling restores structural consistency, DCT-based multi-spectral channel attention emphasizes boundary and texture cues, and a lightweight gate adaptively balances encoder–decoder information. In addition, a top-down feature pyramid is employed to enhance multi-scale representations, and the final decoding stage is strengthened with stacked HR-VSS blocks and coordinate attention for refined spatial localization. Experiments on three public datasets (ISPRS Vaihingen, ISPRS Potsdam, and LoveDA) demonstrate that HRVM-UNet consistently improves segmentation performance and produces sharper object boundaries compared with strong CNN-, Transformer-, and Mamba-based baselines, and our per-class and ablation analyses attribute the gains to the proposed global–local modeling and frequency-aware fusion strategy.

高分辨率遥感语义分割需要同时建模远程空间依赖关系和保持细粒度边界。卷积网络是有效的，但往往难以捕获全局上下文，而变形金刚在大图像上产生二次的自关注成本。为了解决这些问题，我们提出了HRVM-UNet，一个基于视觉曼巴（VMamba）的非对称编码器-解码器分割框架。HRVM-UNet引入了(i)双路径HR-VSS块，该块将选择性扫描状态空间全局路径与多尺度扩展卷积局部路径耦合在一起，从而实现互补的全局-局部表示学习；以及（ii）频率感知跳跃融合（FASF）模块，该模块将跳跃集成制定为空间-频率耦合：carafe风格的内容自适应上采样恢复结构一致性，基于dct的多频谱通道关注强调边界和纹理线索，以及轻量级门自适应平衡编码器-解码器信息。此外，采用自顶向下的特征金字塔来增强多尺度表示，并通过堆叠HR-VSS块和协调注意来加强最终解码阶段，以实现精细的空间定位。在三个公共数据集（ISPRS Vaihingen， ISPRS Potsdam和LoveDA）上的实验表明，与基于CNN， Transformer和mamba的强基线相比，HRVM-UNet持续提高分割性能并产生更清晰的对象边界，我们的每类和消融分析将收益归因于所提出的全局局部建模和频率感知融合策略。

{"title":"HRVM-UNet: Dual-path vision mamba U-Net with frequency-aware skip fusion for high-resolution remote sensing semantic segmentation","authors":"Tao Liu, Xinpei Wang, Yuxuan Deng","doi":"10.1016/j.phycom.2026.103021","DOIUrl":"10.1016/j.phycom.2026.103021","url":null,"abstract":"<div><div>High-resolution remote sensing semantic segmentation requires simultaneously modeling long-range spatial dependencies and preserving fine-grained boundaries. Convolutional networks are efficient but often struggle to capture global context, whereas Transformers incur quadratic self-attention cost on large images. To address these issues, we propose HRVM-UNet, an asymmetric encoder–decoder segmentation framework built upon Vision Mamba (VMamba). HRVM-UNet introduces (i) a dual-path HR-VSS block that couples a selective-scan state-space global path with a multi-scale dilated-convolution local path, enabling complementary global–local representation learning; and (ii) a Frequency-Aware Skip Fusion (FASF) module that formulates skip integration as spatial–frequency coupling: CARAFE-style content-adaptive upsampling restores structural consistency, DCT-based multi-spectral channel attention emphasizes boundary and texture cues, and a lightweight gate adaptively balances encoder–decoder information. In addition, a top-down feature pyramid is employed to enhance multi-scale representations, and the final decoding stage is strengthened with stacked HR-VSS blocks and coordinate attention for refined spatial localization. Experiments on three public datasets (ISPRS Vaihingen, ISPRS Potsdam, and LoveDA) demonstrate that HRVM-UNet consistently improves segmentation performance and produces sharper object boundaries compared with strong CNN-, Transformer-, and Mamba-based baselines, and our per-class and ablation analyses attribute the gains to the proposed global–local modeling and frequency-aware fusion strategy.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 103021"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147397586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Throughput and harvested energy optimization in RIS-assisted multi-user OFDMA-SWIPT systems ris辅助多用户OFDMA-SWIPT系统的吞吐量和收获能量优化

IF 2.2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication

Pub Date : 2026-03-01 Epub Date: 2026-02-04 DOI: 10.1016/j.phycom.2026.103033

Mahendra Tyagi, Sumit Gautam

Reconfigurable Intelligent Surface (RIS) is a promising technology that enables control of a wireless environment to boost system performance. It has attracted attention in the context of beyond 5G (B5G) wireless communication. The demand for power and data in the Internet-of-Things (IoT) applications is envisioned to be fulfilled using RIS with the Simultaneous Wireless Information and Power Transfer (SWIPT) technique. In this paper, we explore RIS-assisted multi-user (MU) orthogonal frequency division multiple access (OFDMA), where users are capable of enabling SWIPT by utilizing either Time Switching (TS) or Power Splitting (PS) protocols of SWIPT. We intend to optimize the performance of RIS-assisted SWIPT-IoT systems, with focus on maximization of two distinct objectives, viz., Sum-Rate and sum-Energy Harvesting (EH), while adhering to Quality-of-Service (QoS) constraints by optimizing the PS/TS factor, sub-carrier assignment matrix, and power allocation to sub-carriers. The proposed alternating optimization-based algorithmic solutions are compared with the asymptotic solution based on the Block Coordinate Descent (BCD) technique while considering the Practical Discrete Phase Shift (PDPS) Model of RIS. It is clear from the results of our simulation that a greater number of RIS elements and sub-carriers is required to achieve a higher throughput and sum-EH.

可重构智能表面（RIS）是一项很有前途的技术，可以通过控制无线环境来提高系统性能。它在超5G （B5G）无线通信的背景下引起了人们的关注。预计物联网（IoT）应用中对电力和数据的需求将通过RIS与同步无线信息和电力传输（SWIPT）技术来实现。在本文中，我们探讨了ris辅助的多用户（MU）正交频分多址（OFDMA），其中用户能够通过使用SWIPT的时间交换（TS）或功率分割（PS）协议来启用SWIPT。我们打算优化ris辅助的swift - iot系统的性能，重点关注两个不同目标的最大化，即求和速率和求和能量收集（EH），同时通过优化PS/TS因子、子载波分配矩阵和子载波的功率分配来坚持服务质量（QoS）约束。将所提出的交替优化算法解与基于块坐标下降（BCD）技术的渐近解进行了比较，并考虑了RIS的实用离散相移（PDPS）模型。从我们的模拟结果可以清楚地看出，需要更多数量的RIS元素和子载波来实现更高的吞吐量和sum-EH。

{"title":"Throughput and harvested energy optimization in RIS-assisted multi-user OFDMA-SWIPT systems","authors":"Mahendra Tyagi, Sumit Gautam","doi":"10.1016/j.phycom.2026.103033","DOIUrl":"10.1016/j.phycom.2026.103033","url":null,"abstract":"<div><div>Reconfigurable Intelligent Surface (RIS) is a promising technology that enables control of a wireless environment to boost system performance. It has attracted attention in the context of beyond 5G (B5G) wireless communication. The demand for power and data in the Internet-of-Things (IoT) applications is envisioned to be fulfilled using RIS with the Simultaneous Wireless Information and Power Transfer (SWIPT) technique. In this paper, we explore RIS-assisted multi-user (MU) orthogonal frequency division multiple access (OFDMA), where users are capable of enabling SWIPT by utilizing either Time Switching (TS) or Power Splitting (PS) protocols of SWIPT. We intend to optimize the performance of RIS-assisted SWIPT-IoT systems, with focus on maximization of two distinct objectives, viz., Sum-Rate and sum-Energy Harvesting (EH), while adhering to Quality-of-Service (QoS) constraints by optimizing the PS/TS factor, sub-carrier assignment matrix, and power allocation to sub-carriers. The proposed alternating optimization-based algorithmic solutions are compared with the asymptotic solution based on the Block Coordinate Descent (BCD) technique while considering the Practical Discrete Phase Shift (PDPS) Model of RIS. It is clear from the results of our simulation that a greater number of RIS elements and sub-carriers is required to achieve a higher throughput and sum-EH.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 103033"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147397926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Techniques for physical layer equalization and monitoring in radio-over-fiber: DSP and machine learning perspectives 光纤无线电中物理层均衡和监控技术：DSP和机器学习的观点

IF 2.2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication

Pub Date : 2026-03-01 Epub Date: 2026-02-03 DOI: 10.1016/j.phycom.2026.103036

César A. Montoya Ocampo, Kevin D. Martinez Zapata, Jhon J. Granada Torres

Radio-over-fiber (RoF) systems are essential to the convergence of optical and wireless networks, serving as key enablers for future high-capacity broadband and 5G/6G applications. However, scaling capacity requires effective strategies for channel equalization and impairment mitigation to overcome complex nonlinearities, particularly at high frequencies. Traditional digital signal processing (DSP) methods are nearing their limits in dynamic scenarios. Thus, this paper addresses a significant lack in the literature by providing a comprehensive bibliometric and systematic analysis to objectively define the evolving roles of established DSP and emerging machine learning (ML) within this critical domain. By analyzing the co-evolution of key research themes, our approach confirms that the field is characterized by a structural coexistence between the two paradigms, rather than simple replacement. The primary results demonstrate that ML techniques, particularly deep learning (DL), establish functional superiority in compensating complex, high-order impairments in high-frequency bands. However, we identify a critical research gap in intelligent monitoring; while ML has high potential for multi-parameter estimation, it remains a niche interest often handled separately across optical and wireless layers. This drives the most pragmatic solution: hybrid DSP+ML architectures. These architectures balance DSP’s computational efficiency, which sets a demanding benchmark for resource consumption, with ML’s intelligence to achieve superior performance under strict cost, size, and power (C-S-P) constraints. The main finding is that this integration is transforming the RoF physical layer, shifting the focus from purely corrective equalization toward predictive, system-level control. The next critical challenges for commercial deployment are the successful implementation of real-time hardware and the standardization of public datasets.

光纤无线电（RoF）系统对于光纤和无线网络的融合至关重要，是未来高容量宽带和5G/6G应用的关键推动因素。然而，缩放能力需要有效的信道均衡和减损策略，以克服复杂的非线性，特别是在高频下。传统的数字信号处理（DSP）方法在动态场景中已经接近极限。因此，本文通过提供全面的文献计量学和系统分析来解决文献中的重大不足，以客观地定义已建立的DSP和新兴机器学习（ML）在这一关键领域中的演变角色。通过分析关键研究主题的共同演变，我们的方法证实了该领域的特征是两种范式之间的结构性共存，而不是简单的替代。初步结果表明，机器学习技术，特别是深度学习（DL），在补偿高频波段复杂的高阶损伤方面具有功能优势。然而，我们在智能监测方面发现了一个关键的研究缺口；虽然机器学习在多参数估计方面具有很高的潜力，但它仍然是一个小众领域，通常在光学和无线层上单独处理。这推动了最实用的解决方案：混合DSP+ML架构。这些架构平衡了DSP的计算效率，这为资源消耗设定了苛刻的基准，而ML的智能可以在严格的成本、尺寸和功耗（C-S-P）限制下实现卓越的性能。主要发现是，这种集成正在改变RoF物理层，将重点从纯粹的校正均衡转向预测性的系统级控制。商业部署的下一个关键挑战是实时硬件的成功实现和公共数据集的标准化。

{"title":"Techniques for physical layer equalization and monitoring in radio-over-fiber: DSP and machine learning perspectives","authors":"César A. Montoya Ocampo, Kevin D. Martinez Zapata, Jhon J. Granada Torres","doi":"10.1016/j.phycom.2026.103036","DOIUrl":"10.1016/j.phycom.2026.103036","url":null,"abstract":"<div><div>Radio-over-fiber (RoF) systems are essential to the convergence of optical and wireless networks, serving as key enablers for future high-capacity broadband and 5G/6G applications. However, scaling capacity requires effective strategies for channel equalization and impairment mitigation to overcome complex nonlinearities, particularly at high frequencies. Traditional digital signal processing (DSP) methods are nearing their limits in dynamic scenarios. Thus, this paper addresses a significant lack in the literature by providing a comprehensive bibliometric and systematic analysis to objectively define the evolving roles of established DSP and emerging machine learning (ML) within this critical domain. By analyzing the co-evolution of key research themes, our approach confirms that the field is characterized by a structural coexistence between the two paradigms, rather than simple replacement. The primary results demonstrate that ML techniques, particularly deep learning (DL), establish functional superiority in compensating complex, high-order impairments in high-frequency bands. However, we identify a critical research gap in intelligent monitoring; while ML has high potential for multi-parameter estimation, it remains a niche interest often handled separately across optical and wireless layers. This drives the most pragmatic solution: hybrid DSP+ML architectures. These architectures balance DSP’s computational efficiency, which sets a demanding benchmark for resource consumption, with ML’s intelligence to achieve superior performance under strict cost, size, and power (C-S-P) constraints. The main finding is that this integration is transforming the RoF physical layer, shifting the focus from purely corrective equalization toward predictive, system-level control. The next critical challenges for commercial deployment are the successful implementation of real-time hardware and the standardization of public datasets.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 103036"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147397929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Boosted HyperNet neural Min-Sum decoder: LDPC error floor mitigation in Space-Air-Ground integrated networks 增强型超网络神经最小和解码器：空-空-地集成网络中的LDPC误差层降低

IF 2.2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication

Pub Date : 2026-03-01 Epub Date: 2026-01-29 DOI: 10.1016/j.phycom.2026.103017

Peiying Zhang , Zheng Feng , Wei Zhang , Huiling Shi , Neeraj Kumar , Jian Wang

Ensuring extremely high reliability and efficiency of communication in dynamic heterogeneous environments is critical for Space-Air-Ground Integrated Networks (SAGIN). To address the error floor phenomenon encountered in low-density parity check (LDPC) codes, we design an innovative decoder based on HyperNet and boosted learning: boosted HyperNet Neural Min-Sum (BHNMS) decoder. This decoder features: (1) Layered Activation Mechanism dynamically activates HyperNet to solve the explosion of training resources due to forward computation required for HyperNet, multi-stage training for boosted learning, and block-wise iterative chunk training; (2) Quantization-aware weight generation relies on differentiable quantization gates, dynamic precision-aware training, and quantization domain consistency constraints to solve the compatibility disconnect between HyperNet’s floating-point computation and quantization weight generation; (3) Cross-stage State Relay achieves continuous reconstruction of node evolution trajectories across stages through spatiotemporal compression transmission and adaptive accuracy control to solve the dynamic feedback imbalance issue; (4) Block Gradient Bridge reconstructs the global gradient propagation path through learnable bridge parameters and cross-block consistency constraints, ensuring the end-to-end trainability of dynamic weight generators to solve the problem of gradient propagation disruption. Simulation shows that BHNMS does not exhibit significant error floors, and its performance far exceeds that of traditional decoders, reaching

10^{- 9}

earlier

在动态异构环境中确保极高的通信可靠性和效率对天空地一体化网络（SAGIN）至关重要。为了解决低密度奇偶校验（LDPC）码中遇到的错误层现象，我们设计了一种基于HyperNet和增强学习的创新解码器：增强的HyperNet神经最小和（BHNMS）解码器。该解码器具有以下特点：(1)分层激活机制动态激活HyperNet，解决HyperNet需要前向计算、多阶段训练促进学习、分块迭代块训练带来的训练资源爆炸问题；(2)量化感知权值生成依赖于可微量化门、动态精度感知训练和量化域一致性约束，解决了HyperNet浮点计算与量化权值生成之间的兼容性脱节；(3)跨阶段状态中继通过时空压缩传输和自适应精度控制实现节点演化轨迹跨阶段的连续重构，解决动态反馈不平衡问题；(4)块梯度桥通过可学习的桥参数和跨块一致性约束重构全局梯度传播路径，保证动态权值生成器端到端的可训练性，解决梯度传播中断问题。仿真结果表明，BHNMS没有明显的误差层，其性能远远超过传统的解码器，达到10−9

{"title":"Boosted HyperNet neural Min-Sum decoder: LDPC error floor mitigation in Space-Air-Ground integrated networks","authors":"Peiying Zhang , Zheng Feng , Wei Zhang , Huiling Shi , Neeraj Kumar , Jian Wang","doi":"10.1016/j.phycom.2026.103017","DOIUrl":"10.1016/j.phycom.2026.103017","url":null,"abstract":"<div><div>Ensuring extremely high reliability and efficiency of communication in dynamic heterogeneous environments is critical for Space-Air-Ground Integrated Networks (SAGIN). To address the error floor phenomenon encountered in low-density parity check (LDPC) codes, we design an innovative decoder based on HyperNet and boosted learning: boosted HyperNet Neural Min-Sum (BHNMS) decoder. This decoder features: (1) Layered Activation Mechanism dynamically activates HyperNet to solve the explosion of training resources due to forward computation required for HyperNet, multi-stage training for boosted learning, and block-wise iterative chunk training; (2) Quantization-aware weight generation relies on differentiable quantization gates, dynamic precision-aware training, and quantization domain consistency constraints to solve the compatibility disconnect between HyperNet’s floating-point computation and quantization weight generation; (3) Cross-stage State Relay achieves continuous reconstruction of node evolution trajectories across stages through spatiotemporal compression transmission and adaptive accuracy control to solve the dynamic feedback imbalance issue; (4) Block Gradient Bridge reconstructs the global gradient propagation path through learnable bridge parameters and cross-block consistency constraints, ensuring the end-to-end trainability of dynamic weight generators to solve the problem of gradient propagation disruption. Simulation shows that BHNMS does not exhibit significant error floors, and its performance far exceeds that of traditional decoders, reaching <span><math><msup><mn>10</mn><mrow><mo>−</mo><mn>9</mn></mrow></msup></math></span> earlier</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 103017"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147397950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving rainfall retrieval accuracy using cross-Modal deep learning: Merging wifi with commercial microwave link 利用跨模态深度学习提高降雨检索精度：将wifi与商用微波链路融合

IF 2.2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication

Pub Date : 2026-03-01 Epub Date: 2026-01-30 DOI: 10.1016/j.phycom.2026.103014

Weitao Tao , Bin Lian , Zhongcheng Wei , Luming Song , Lili Huang , Jijun Zhao

Commercial microwave links (CMLs) have attracted increasing attention in meteorology and hydrology as a cost-effective method for rainfall retrieval. Nevertheless, the typical single-link and high-frequency structure of CMLs often limits the accuracy of rainfall retrieval. This study proposes a cross-modal deep learning model that merges channel state information (CSI) from WiFi with received signal level (RSL) from CMLs for high-precision rainfall retrieval. First, a fast dynamic time warping algorithm is applied to align the RSL and CSI data. The CSI data are then denoised and filtered using wavelet denoising and Savitzky-Golay filtering. At the same time, the RSL data undergo feature engineering, including gradient extraction, rolling statistics, and wavelet-based features. A gated cross-modal attention mechanism is then utilized for feature-level fusion, and a dynamic weighted network adaptively adjusts the contribution of each modality. Finally, a decision-level fusion module with consistency regularization generates the final rainfall intensity estimates. Experimental results demonstrate that the proposed model achieves a pearson correlation coefficient of 0.9541, a root mean square error of 0.0271 mm/h, a coefficient of variation of 1.8948, and a relative bias of -30.4%, confirming its effectiveness in improving rainfall retrieval accuracy through WiFi-CML data fusion.

商用微波链路作为一种经济有效的降雨检索方法，在气象学和水文学领域受到越来越多的关注。然而，cml典型的单链路和高频结构往往限制了降水反演的准确性。本研究提出了一种跨模态深度学习模型，该模型将来自WiFi的信道状态信息（CSI）与来自cml的接收信号电平（RSL）合并，用于高精度降雨检索。首先，采用快速动态时间规整算法对RSL和CSI数据进行对齐。然后使用小波去噪和Savitzky-Golay滤波对CSI数据进行去噪和滤波。同时，对RSL数据进行特征工程处理，包括梯度提取、滚动统计和基于小波的特征。然后利用门控跨模态注意机制进行特征级融合，动态加权网络自适应调整各模态的贡献。最后，采用一致性正则化的决策级融合模块生成最终的降雨强度估计。实验结果表明，该模型的pearson相关系数为0.9541，均方根误差为0.0271 mm/h，变异系数为1.8948，相对偏差为-30.4%，验证了该模型通过WiFi-CML数据融合提高降雨检索精度的有效性。

{"title":"Improving rainfall retrieval accuracy using cross-Modal deep learning: Merging wifi with commercial microwave link","authors":"Weitao Tao , Bin Lian , Zhongcheng Wei , Luming Song , Lili Huang , Jijun Zhao","doi":"10.1016/j.phycom.2026.103014","DOIUrl":"10.1016/j.phycom.2026.103014","url":null,"abstract":"<div><div>Commercial microwave links (CMLs) have attracted increasing attention in meteorology and hydrology as a cost-effective method for rainfall retrieval. Nevertheless, the typical single-link and high-frequency structure of CMLs often limits the accuracy of rainfall retrieval. This study proposes a cross-modal deep learning model that merges channel state information (CSI) from WiFi with received signal level (RSL) from CMLs for high-precision rainfall retrieval. First, a fast dynamic time warping algorithm is applied to align the RSL and CSI data. The CSI data are then denoised and filtered using wavelet denoising and Savitzky-Golay filtering. At the same time, the RSL data undergo feature engineering, including gradient extraction, rolling statistics, and wavelet-based features. A gated cross-modal attention mechanism is then utilized for feature-level fusion, and a dynamic weighted network adaptively adjusts the contribution of each modality. Finally, a decision-level fusion module with consistency regularization generates the final rainfall intensity estimates. Experimental results demonstrate that the proposed model achieves a pearson correlation coefficient of 0.9541, a root mean square error of 0.0271 mm/h, a coefficient of variation of 1.8948, and a relative bias of -30.4%, confirming its effectiveness in improving rainfall retrieval accuracy through WiFi-CML data fusion.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 103014"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147397952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robust secure transmission for STAR-RIS assisted ISAC against collaborative eavesdropper with imperfect CSI STAR-RIS辅助ISAC抗不完美CSI协同窃听的鲁棒安全传输

IF 2.2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication

Pub Date : 2026-03-01 Epub Date: 2026-01-16 DOI: 10.1016/j.phycom.2026.103011

Jialing Xu , Jianbin Xue , Han Zhang , Xiangrui Guan

Integrated sensing and communication (ISAC), especially when assisted by simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS), is a key technology for improving spectrum efficiency in future sixth-generation (6 G) networks. However, the inherent open and broadcast nature of wireless channels makes such systems vulnerable to eavesdropping by malicious users. Existing secure transmission schemes often overlook the severe threats posed by cooperative eavesdroppers (Eve), and many studies commonly assume that the channel state information (CSI) of Eve is perfectly known, which is unrealistic in practice. This paper investigates the problem of physical layer security (PLS) transmission in a downlink ISAC system assisted by a STAR-RIS. We consider a challenging scenario in which the dual regions of the STAR-RIS serve a sensing target (ST) and communication users, respectively, while facing the worst-case security threat caused by cooperative Eves on both sides. In addition, due to the practical difficulty in obtaining perfect CSI of the Eves, we formulate a secrecy rate maximization problem under imperfect CSI, while considering both the quality of service (QoS) requirement of communication users and the sensing performance constraint. To solve this highly non-convex optimization problem, a deep reinforcement learning (DRL) method based on the soft actor–critic (SAC) algorithm is developed, which can dynamically search for the optimal strategy for secure transmission. Numerical results illustrate that the proposed scheme keeps a good balance between sensing, communication, and security performance. Moreover, it exhibits strong robustness against cooperative Eves and uncertain CSI.

集成传感和通信（ISAC），特别是在同时传输和反射可重构智能表面（STAR-RIS）的辅助下，是提高未来第六代（6g）网络频谱效率的关键技术。然而，无线信道固有的开放性和广播性使得这种系统容易受到恶意用户的窃听。现有的安全传输方案往往忽视了合作窃听者（Eve）带来的严重威胁，许多研究通常假设Eve的信道状态信息（CSI）是完全已知的，这在实践中是不现实的。本文研究了由STAR-RIS辅助的下行ISAC系统的物理层安全传输问题。我们考虑了一个具有挑战性的场景，其中STAR-RIS的双区域分别为传感目标（ST）和通信用户服务，同时面临双方合作Eves造成的最坏安全威胁。此外，由于在实际应用中难以获得Eves的完美CSI，我们在考虑通信用户的服务质量（QoS）需求和感知性能约束的情况下，提出了不完美CSI下的保密率最大化问题。为了解决这一高度非凸优化问题，提出了一种基于软行为者评价（SAC）算法的深度强化学习（DRL）方法，该方法可以动态搜索安全传输的最优策略。数值结果表明，该方案在传感、通信和安全性能之间保持了良好的平衡。此外，该方法对合作Eves和不确定CSI具有较强的鲁棒性。

{"title":"Robust secure transmission for STAR-RIS assisted ISAC against collaborative eavesdropper with imperfect CSI","authors":"Jialing Xu , Jianbin Xue , Han Zhang , Xiangrui Guan","doi":"10.1016/j.phycom.2026.103011","DOIUrl":"10.1016/j.phycom.2026.103011","url":null,"abstract":"<div><div>Integrated sensing and communication (ISAC), especially when assisted by simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS), is a key technology for improving spectrum efficiency in future sixth-generation (6 G) networks. However, the inherent open and broadcast nature of wireless channels makes such systems vulnerable to eavesdropping by malicious users. Existing secure transmission schemes often overlook the severe threats posed by cooperative eavesdroppers (Eve), and many studies commonly assume that the channel state information (CSI) of Eve is perfectly known, which is unrealistic in practice. This paper investigates the problem of physical layer security (PLS) transmission in a downlink ISAC system assisted by a STAR-RIS. We consider a challenging scenario in which the dual regions of the STAR-RIS serve a sensing target (ST) and communication users, respectively, while facing the worst-case security threat caused by cooperative Eves on both sides. In addition, due to the practical difficulty in obtaining perfect CSI of the Eves, we formulate a secrecy rate maximization problem under imperfect CSI, while considering both the quality of service (QoS) requirement of communication users and the sensing performance constraint. To solve this highly non-convex optimization problem, a deep reinforcement learning (DRL) method based on the soft actor–critic (SAC) algorithm is developed, which can dynamically search for the optimal strategy for secure transmission. Numerical results illustrate that the proposed scheme keeps a good balance between sensing, communication, and security performance. Moreover, it exhibits strong robustness against cooperative Eves and uncertain CSI.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 103011"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147397956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

STAR-RIS-empowered hybrid NOMA/OMA with adaptive modulation for URLLC in finite-blocklength V2X-communications 基于star - ris的混合NOMA/OMA自适应调制在有限块长度v2x通信中的URLLC

IF 2.2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication

Pub Date : 2026-03-01 Epub Date: 2026-02-05 DOI: 10.1016/j.phycom.2026.103041

Sanjay Bhardwaj, Won Jae Ryu, Dong-Seong Kim

This paper proposes a novel STAR-RIS-assisted hybrid NOMA/OMA framework with adaptive modulation (AM) for ultra-reliable low-latency vehicle-to-everything (V2X) communications under finite blocklength (FBL) constraints. Unlike existing works that separately address STAR-RIS optimization, hybrid multiple access, or URLLC modeling, this study jointly integrates AM, dynamic NOMA/OMA mode switching, and mobility-aware STAR-RIS beam control into a unified FBL-aware design. A roadside unit (RSU) serves a pair of vehicular users with heterogeneous channel conditions, where a STAR-RIS simultaneously transmits and reflects signals to enhance coverage and reliability in high-mobility environments. The core motivation is to overcome the inaccuracy of infinite blocklength assumptions and the rigidity of fixed-access schemes when meeting stringent URLLC latency–reliability requirements. Closed-form reliability expressions are derived for both NOMA and OMA modes under short-packet transmission, explicitly capturing decoding errors, channel dispersion, and imperfect channel state information (CSI). A joint optimization framework based on fractional programming and K-means user clustering is developed to adapt power allocation, modulation order, and access mode selection.Simulation results demonstrate that the proposed SR-AM-URLLC-V2X framework achieves up to 25% higher sum rate, ultra-high reliability (

ϵ_{k} \leq 10^{- 5}

) at practical SNR levels, and robust performance under vehicular speeds up to 100 km/h, compared to conventional RIS-assisted and fixed-access V2X schemes. These results highlight its effectiveness for safety-critical URLLC-driven V2X communications.

本文提出了一种具有自适应调制（AM）的新型star - ris辅助混合NOMA/OMA框架，用于有限块长度（FBL）约束下的超可靠低延迟车对万物（V2X）通信。与现有的单独解决STAR-RIS优化、混合多址或URLLC建模的工作不同，本研究将AM、动态NOMA/OMA模式切换和机动感知STAR-RIS波束控制集成到统一的fbl感知设计中。路旁单元（RSU）服务于具有异构信道条件的一对车载用户，其中STAR-RIS同时传输和反射信号，以增强高机动性环境中的覆盖范围和可靠性。其核心动机是克服无限块长度假设的不准确性和固定访问方案的刚性，同时满足严格的URLLC延迟可靠性要求。推导了短包传输下NOMA和OMA模式的封闭式可靠性表达式，显式捕获解码错误、信道分散和不完全信道状态信息（CSI）。提出了一种基于分数规划和K-means用户聚类的联合优化框架，以适应功率分配、调制顺序和接入方式的选择。仿真结果表明，与传统的ris辅助和固定接入V2X方案相比，所提出的SR-AM-URLLC-V2X框架在实际信噪比水平下实现了高达25%的求和速率，超高可靠性（ϵk≤10−5），以及在车速高达100 km/h下的稳健性能。这些结果突出了其在安全关键的url驱动V2X通信中的有效性。

{"title":"STAR-RIS-empowered hybrid NOMA/OMA with adaptive modulation for URLLC in finite-blocklength V2X-communications","authors":"Sanjay Bhardwaj, Won Jae Ryu, Dong-Seong Kim","doi":"10.1016/j.phycom.2026.103041","DOIUrl":"10.1016/j.phycom.2026.103041","url":null,"abstract":"<div><div>This paper proposes a novel STAR-RIS-assisted hybrid NOMA/OMA framework with adaptive modulation (AM) for ultra-reliable low-latency vehicle-to-everything (V2X) communications under finite blocklength (FBL) constraints. Unlike existing works that separately address STAR-RIS optimization, hybrid multiple access, or URLLC modeling, this study jointly integrates AM, dynamic NOMA/OMA mode switching, and mobility-aware STAR-RIS beam control into a unified FBL-aware design. A roadside unit (RSU) serves a pair of vehicular users with heterogeneous channel conditions, where a STAR-RIS simultaneously transmits and reflects signals to enhance coverage and reliability in high-mobility environments. The core motivation is to overcome the inaccuracy of infinite blocklength assumptions and the rigidity of fixed-access schemes when meeting stringent URLLC latency–reliability requirements. Closed-form reliability expressions are derived for both NOMA and OMA modes under short-packet transmission, explicitly capturing decoding errors, channel dispersion, and imperfect channel state information (CSI). A joint optimization framework based on fractional programming and K-means user clustering is developed to adapt power allocation, modulation order, and access mode selection.Simulation results demonstrate that the proposed SR-AM-URLLC-V2X framework achieves up to 25% higher sum rate, ultra-high reliability (<span><math><mrow><msub><mi>ϵ</mi><mi>k</mi></msub><mo>≤</mo><msup><mn>10</mn><mrow><mo>−</mo><mn>5</mn></mrow></msup></mrow></math></span>) at practical SNR levels, and robust performance under vehicular speeds up to 100 km/h, compared to conventional RIS-assisted and fixed-access V2X schemes. These results highlight its effectiveness for safety-critical URLLC-driven V2X communications.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 103041"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147397959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Covert underwater acoustic communication: Joint spectral mimicry and soft-Limiting peak suppression 隐蔽水声通信：联合频谱模拟和软限制峰值抑制

IF 2.2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication

Pub Date : 2026-03-01 Epub Date: 2026-01-17 DOI: 10.1016/j.phycom.2026.103009

Ebrahim Raeisian Dashtaki , Ehsan Moradi , Mohammadreza Jalili

The broadcast nature of underwater acoustic channels necessitates low probability of detection communication to secure critical sensor networks. This paper proposes a hardware-aware steganographic transceiver that reconciles high reliability with strict covertness constraints under practical hardware impairments. To ensure reliable transmission amidst severe multipath fading, we adopt an orthogonal frequency division multiplexing framework. However, practical deployment faces challenges from the high peak-to-average power ratio and hardware non-idealities, including in-phase/quadrature imbalance and residual hardware impairments. Our architecture addresses these by disguising the signal via Wenz-based spectral amplitude shaping and random phase scrambling to mimic ambient ocean noise. Furthermore, we introduce a symmetric frequency diversity scheme that transforms in-phase/quadrature imbalance-induced interference into constructive diversity gain and employ a soft-limiting suppression mechanism based on a hyperbolic-tangent profile. This technique smoothly compresses signal peaks to a target of 7 dB, mitigating non-linear distortion while preserving the Gaussian statistical integrity of the cover signal. Simulation results demonstrate that the proposed system can achieve a bit error rate

< 10^{- 2}

across transmission ranges from 100 m to 7 km. The effective data rate is scalable between 3.31 kbps and 52 bps, while maintaining a negligible Kullback-Leibler divergence ( ≈ 0.03) relative to the Gaussian background noise, validating its feasibility for hardware-constrained underwater covert operations.

水声信道的广播性质要求低探测通信概率以保证关键传感器网络的安全。本文提出了一种硬件感知的隐写收发器，该收发器在实际硬件缺陷的情况下能够兼顾高可靠性和严格的隐蔽性约束。为了保证在严重多径衰落情况下的可靠传输，我们采用了正交频分复用框架。然而，实际部署面临着来自高峰值平均功率比和硬件非理想性的挑战，包括同相/正交不平衡和剩余的硬件损伤。我们的架构通过基于wenz的频谱幅度整形和随机相位置乱来模拟环境海洋噪声来掩盖信号，从而解决了这些问题。此外，我们还引入了一种对称频率分集方案，该方案将同相/正交不平衡引起的干扰转换为建设性分集增益，并采用了基于双曲-切线轮廓的软限制抑制机制。该技术平滑地将信号峰值压缩到7 dB的目标，减轻了非线性失真，同时保持了覆盖信号的高斯统计完整性。仿真结果表明，该系统在100 ~ 7 km的传输范围内可以实现10−2的误码率。有效数据速率可在3.31 kbps和52 bps之间扩展，同时相对于高斯背景噪声保持可忽略的kullbackleibler散度（ ≈ 0.03），验证了其在硬件受限的水下隐蔽操作中的可行性。

{"title":"Covert underwater acoustic communication: Joint spectral mimicry and soft-Limiting peak suppression","authors":"Ebrahim Raeisian Dashtaki , Ehsan Moradi , Mohammadreza Jalili","doi":"10.1016/j.phycom.2026.103009","DOIUrl":"10.1016/j.phycom.2026.103009","url":null,"abstract":"<div><div>The broadcast nature of underwater acoustic channels necessitates low probability of detection communication to secure critical sensor networks. This paper proposes a hardware-aware steganographic transceiver that reconciles high reliability with strict covertness constraints under practical hardware impairments. To ensure reliable transmission amidst severe multipath fading, we adopt an orthogonal frequency division multiplexing framework. However, practical deployment faces challenges from the high peak-to-average power ratio and hardware non-idealities, including in-phase/quadrature imbalance and residual hardware impairments. Our architecture addresses these by disguising the signal via Wenz-based spectral amplitude shaping and random phase scrambling to mimic ambient ocean noise. Furthermore, we introduce a symmetric frequency diversity scheme that transforms in-phase/quadrature imbalance-induced interference into constructive diversity gain and employ a soft-limiting suppression mechanism based on a hyperbolic-tangent profile. This technique smoothly compresses signal peaks to a target of 7 dB, mitigating non-linear distortion while preserving the Gaussian statistical integrity of the cover signal. Simulation results demonstrate that the proposed system can achieve a bit error rate <span><math><mrow><mo><</mo><msup><mn>10</mn><mrow><mo>−</mo><mn>2</mn></mrow></msup></mrow></math></span> across transmission ranges from 100 m to 7 km. The effective data rate is scalable between 3.31 kbps and 52 bps, while maintaining a negligible Kullback-Leibler divergence ( ≈ 0.03) relative to the Gaussian background noise, validating its feasibility for hardware-constrained underwater covert operations.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 103009"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146024417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

首页上一页

下一页尾页

类型

全部化学•材料生命科学医学物理工程技术环境•农林材料科学地球科学法学管理学化学环境科学与生态学计算机科学教育学经济学农林科学人文科学生物学数学物理与天体物理心理学综合性期刊其他工业工程理学历史学农学文学信息工程

数据库

全部 ACS Publications Elsevier ieeexplore Springer The Royal Society of Chemistry Wiley

期刊

Physical Communication

全部 Big Earth Data Adv. Meteorol. ENTROPY-SWITZ IZV-PHYS SOLID EART+ Ann. Phys. 2011 International Conference on Electrical and Control Engineering Ecol. Res. J. Atmos. Chem. 2011 Annual Report Conference on Electrical Insulation and Dielectric Phenomena ACTA ORTHOP Geol. J. Engineering Science and Technology, an International Journal Environ. Eng. Manage. J. Archaeol. Anthropol. Sci. Ecol. Indic. Nat. Hazards Earth Syst. Sci. Int. Geol. Rev. AAPG Bull. Geophys. Prospect. Chin. Phys. B J. Nanophotonics Int. J. Astrobiol. INT J MOD PHYS B 2009 16th International Conference on Industrial Engineering and Engineering Management 2008 IEEE 35th International Conference on Plasma Science 2009 International Conference on Energy and Environment Technology 2010 International Conference on Mechanic Automation and Control Engineering J. Phys. Soc. Jpn. ACTA HAEMATOL-BASEL ACTA OBSTET GYN SCAN Acta Neuropsychiatr. ARCH ACOUST PETROLOGY+ Intereconomics Environ. Educ. Res, "Laboratorio;" analisis clinicos, bacteriologia, inmunologia, parasitologia, hematologia, anatomia patologica, quimica clinica Contrib. Mineral. Petrol. J. Atmos. Oceanic Technol. PERIOD MINERAL Energy Ecol Environ Eurasian Physical Technical Journal 2013 IEEE International Interconnect Technology Conference - IITC Rev. Geophys. Hydrol. Processes NANOPHOTONICS-BERLIN Acta Trop. Environmental dermatology : the official journal of the Japanese Society for Contact Dermatitis Int. J. Biometeorol. J PHYS D APPL PHYS Aust. J. Earth Sci. Clean-Soil Air Water Atmos. Meas. Tech. Annu. Rev. Earth Planet. Sci. Geostand. Geoanal. Res. Geobiology Asia-Pac. J. Atmos. Sci. 2010 3rd International Nanoelectronics Conference (INEC) Azerbaidzhanskii Meditsinskii Zhurnal ARCHAEOMETRY Adv. Atmos. Sci. Clim. Change Contrib. Plasma Phys. J. Meteorolog. Res. Am. Mineral. ARCT ANTARCT ALP RES Chin. J. Phys. Atmos. Res. 2013 International Conference on Optical MEMS and Nanophotonics (OMN) ACTA GEOL POL 2010 IEEE International Symposium on Hardware-Oriented Security and Trust (HOST) Astrophys. Space Sci. Am. J. Sci. Clean Technol. Environ. Policy Acta Oceanolog. Sin. 2011 VII Southern Conference on Programmable Logic (SPL) Ecol. Processes EUR PHYS J-SPEC TOP ENVIRON GEOL Geochim. Cosmochim. Acta 2013 IEEE MTT-S International Microwave Workshop Series on RF and Wireless Technologies for Biomedical and Healthcare Applications (IMWS-BIO) ATMOSPHERE-BASEL Appl. Phys. Rev. Aquat. Geochem. Ann. Glaciol. CHIN OPT LETT Appl. Clay Sci. ECOLOGY Geosci. J. Environ. Prog. Sustainable Energy Geosci. Model Dev. Org. Geochem. Front. Phys. Carbon Balance Manage. ADV MED SCI-POLAND Chem. Ecol. Basin Res. Chin. Phys. C Am. J. Phys. Anthropol. Atmos. Chem. Phys. ASTRON ASTROPHYS

﹀