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IF 4.3 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Computer Communications

Pub Date : 2026-01-01

引用次数: 0

IF 4.3 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Computer Communications

Pub Date : 2026-01-01

引用次数: 0

IF 4.3 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Computer Communications

Pub Date : 2026-01-01

引用次数: 0

IF 4.3 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Computer Communications

Pub Date : 2026-01-01

引用次数: 0

Joint design of resource allocation and QoS enhancement via serial optimization in UAV-NOMA communications 基于串行优化的无人机- noma通信资源分配与QoS增强联合设计

IF 4.3 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Computer Communications

Pub Date : 2025-12-30 DOI: 10.1016/j.comcom.2025.108409

Zhongyu Wang , Yanan Lian , Jie Zeng , Zheng Chang , Tiejun Lv

We investigate the challenges of user pairing, power allocation, and bandwidth allocation problems in unmanned aerial vehicle (UAV) systems that employ nonorthogonal multiple access (NOMA) for communication with multiple ground users. The primary objective is to maximize the system’s achievable transmission rate while ensuring the users’ quality of service (QoS) requirements under a constrained total power budget. Considering the nonconvexity of the original problem and the interdependencies among multiple optimization variables, the problem is decomposed into three subproblems to optimize power and bandwidth allocation. To increase resource utilization and address user pairing challenges, a serial-optimized communication scheme is proposed, which leverages an optimized block coordinate descent (OP-BCD) method to sequentially solve the subproblems. Specifically, the power allocation strategy is optimized using an optimized deep Q-network (DQN) combined with a gradient ascent approach, whereas the intergroup bandwidth is optimized via a sequential least squares programming (SLSQP). Simulation results demonstrate that the proposed group matching method significantly enhances resource utilization and fairness compared to other user pairing strategies. Moreover, the proposed scheme effectively increases the system transmission rate and resource efficiency.

本文研究了采用非正交多址（NOMA）与多个地面用户通信的无人机系统中的用户配对、功率分配和带宽分配问题。主要目标是在有限的总功率预算下，在保证用户服务质量（QoS）需求的同时，最大限度地提高系统可实现的传输速率。考虑到原问题的非凸性和多个优化变量之间的相互依赖性，将问题分解为三个子问题，对功率和带宽分配进行优化。为了提高资源利用率和解决用户配对难题，提出了一种串行优化通信方案，该方案利用优化块坐标下降（OP-BCD）方法对子问题进行顺序求解。具体而言，采用优化的深度q网络（DQN）和梯度上升方法对功率分配策略进行优化，而通过顺序最小二乘规划（SLSQP）对群间带宽进行优化。仿真结果表明，与其他用户配对策略相比，所提出的分组匹配方法显著提高了资源利用率和公平性。此外，该方案有效地提高了系统传输速率和资源效率。

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引用次数: 0

Making cellular networks crisis-proof: Towards island-ready, resilient-by-design 6G communication networks 使蜂窝网络防危机：迈向孤岛就绪、设计弹性的6G通信网络

IF 4.3 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Computer Communications

Pub Date : 2025-12-30 DOI: 10.1016/j.comcom.2025.108407

Leon Janzen, Matthias Hollick

5G and 5G-Advanced cellular networks are vulnerable to local outages resulting from disasters or targeted attacks. This fragility stems from the reliance on the central core network involved for most 5G connectivity use cases. Crisis-struck areas isolated from the cellular core network form islands, where crisis response is hindered by the unavailability of recovery-relevant services, such as emergency calls, cell broadcasts, messengers, and news apps. Our concept of island-ready, resilient-by-design 6G communication networks envisions local cellular connectivity allowing users to connect to local application servers, which is currently impossible. In our conceptualization, we follow an all-society approach, as realizing island connectivity requires the cooperation of multiple actors, including users, operators, developers, providers, and authorities. We evaluate the island readiness of 5G and 5G-Advanced systems and outline the open challenges stakeholders must address for full island readiness, such as decentralizing the 6G core network and designing local-first application architectures.

5G和5G- advanced蜂窝网络很容易受到灾难或有针对性攻击造成的局部中断的影响。这种脆弱性源于对大多数5G连接用例所涉及的中央核心网络的依赖。与蜂窝核心网络隔离的受危机影响地区形成孤岛，由于无法获得与恢复相关的服务，如紧急呼叫、蜂窝广播、信使和新闻应用程序，危机应对受到阻碍。我们的概念是孤岛就绪，设计灵活的6G通信网络，设想本地蜂窝连接允许用户连接到本地应用服务器，这是目前不可能的。在我们的概念中，我们遵循全社会的方法，因为实现岛屿连接需要多个参与者的合作，包括用户、运营商、开发商、提供商和当局。我们评估了5G和5G- advanced系统的孤岛准备情况，并概述了利益相关者必须解决的开放挑战，以实现完全的孤岛准备，例如分散6G核心网络和设计本地优先的应用架构。

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引用次数: 0

MetaHeart: Metasurface enabled biometrics camouflage MetaHeart: metassurface启用生物识别伪装

IF 4.3 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Computer Communications

Pub Date : 2025-12-27 DOI: 10.1016/j.comcom.2025.108405

Dora Zivanovic , Jy-Chin Liao , Zhambyl Shaikhanov , Hou-Tong Chen , Chun-Chieh Chang , Sadhvikas Addamane , Daniel M. Mittleman , Edward W. Knightly

Privacy-invading biometrics monitoring is becoming a prominent security threat as modern sensing systems move to higher operating frequencies (mmWave, sub-THz), increasing sensing resolution and accuracy. As such, developing systems that can protect or obfuscate biometrics from adversarial intrusion becomes pivotal to preserving user privacy. In this work, we develop and implement MetaHeart, a real-time biometrics misinformation system based on reflective, programmable metasurfaces and dynamic phase-front manipulation of radar inferences. MetaHeart’s key goal is to prevent the leakage of a legitimate user’s heartbeat biometrics by spoofing fake heartbeat signals at a malicious, radar-equipped, heart rate sensing intruder. We experimentally demonstrate MetaHeart’s ability to fake Alice’s presence when she is not there and to fool Trudy’s inferences even when Alice is present, achieving an overall accuracy above 98%. Finally, we conduct a robustness analysis to determine MetaHeart’s required spatial placement within the intruder’s monitoring area that would allow for effective spoofing.

随着现代传感系统向更高的工作频率（毫米波、次太赫兹）移动，传感分辨率和精度不断提高，侵犯隐私的生物识别监测正成为一个突出的安全威胁。因此，开发能够保护或混淆生物识别技术免受敌对入侵的系统对于保护用户隐私至关重要。在这项工作中，我们开发并实现了MetaHeart，这是一个基于反射、可编程元表面和雷达推断的动态相位前操作的实时生物识别错误信息系统。MetaHeart的主要目标是通过欺骗伪造的心跳信号，防止合法用户的心跳生物识别信息泄露给恶意的、配备雷达的心率感应入侵者。我们通过实验证明，MetaHeart能够在爱丽丝不在场的时候假装她的存在，即使在爱丽丝在场的时候也能欺骗特鲁迪的推断，总体准确率超过98%。最后，我们进行了鲁棒性分析，以确定MetaHeart在入侵者监控区域内所需的空间位置，从而允许有效的欺骗。

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引用次数: 0

Making TCP IoT-friendly towards the 6G era 面向6G时代，使TCP物联网友好

IF 4.3 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Computer Communications

Pub Date : 2025-12-27 DOI: 10.1016/j.comcom.2025.108406

Carles Gomez , Jon Crowcroft

Traditionally, Internet of Things (IoT) communication technologies have been designed to offer low bit rates (from ∼10² to ∼10⁶ bit/s). However, recent IoT-intended technologies like 5G Reduced Capability (RedCap) support significantly greater bit rates (up to ∼10⁸ bit/s), enabling emerging IoT use cases that demand greater capacity. Thus, the spectrum of IoT scenarios and corresponding requirements is expanding, a trend which is expected to continue with 6G networks. In this context, support, configuration and performance of a crucial upper-layer protocol like TCP become challenging. In this paper, based on our IETF standardization work, we describe how TCP can run suitably on a wide variety of IoT environments (from highly constrained scenarios to resource-rich ones). Furthermore, we present and study the novel TCP option called TCP Acknowledgment Rate Request (TARR), designed for further TCP adaptability, which is particularly useful for current and future IoT networks.

传统上，物联网（IoT）通信技术被设计为提供低比特率（从~ 102到~ 106比特/秒）。然而，最近的物联网技术，如5G低容量（RedCap），支持更高的比特率（高达~ 108比特/秒），使新兴的物联网用例需要更大的容量。因此，物联网场景的范围和相应的需求正在扩大，预计6G网络将继续这一趋势。在这种情况下，像TCP这样重要的上层协议的支持、配置和性能变得具有挑战性。在本文中，基于我们的IETF标准化工作，我们描述了TCP如何在各种物联网环境（从高度受限的场景到资源丰富的场景）上适当地运行。此外，我们提出并研究了一种新的TCP选项，称为TCP确认率请求（TARR），旨在进一步提高TCP的适应性，这对当前和未来的物联网网络特别有用。

引用次数: 0

Joint optimization of UAV trajectory, RIS selection, and offloading strategy for RIS-assisted UAV-MEC systems based on DRL 基于DRL的RIS辅助UAV- mec系统航迹、RIS选择及卸载策略联合优化

IF 4.3 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Computer Communications

Pub Date : 2025-12-24 DOI: 10.1016/j.comcom.2025.108402

Jianhua Liu , Bo Tang , Jiajia Liu , Xia Lei , Xiaoguang Tu , Xiaofan Wang

The Mobile Edge Computing (MEC) system equipped with servers on Unmanned Aerial Vehicle (UAV) is an effective solution for computing offloading in the absence of communication resource infrastructure. Introducing Reconfigurable Intelligent Surfaces (RIS) into the UAV-MEC system can enhance air-to-ground communication quality and optimize Non-Line-of-Sight (N-LoS) links. However, how to dynamically select service users for the RIS based on environmental changes, so as to reduce signal interference and improve resource utilization, remains a key challenge to be addressed. To tackle this issue, we aim to jointly optimize the three-dimensional (3D) trajectory of UAV, RIS selection decisions, and task offloading strategy to minimize the overall system delay. Due to the non-convexity of the joint problem, it is difficult to solve it efficiently using traditional optimization methods. Therefore, this paper proposes a Hybrid Exploration Deep Deterministic Policy Gradient (HEDDPG) algorithm based on Deep Reinforcement Learning (DRL). By integrating random exploration into the original DDPG framework, the proposed algorithm enhances global search capability in complex environments. The experimental results show that with the addition of RIS assistance, the system delay is reduced by 18.8%. Compared to other benchmark algorithms, HEDDPG performs better, achieving efficient strategy optimization for the system and improving the performance of communication links and resource utilization efficiency.

在无人机（UAV）上配备服务器的移动边缘计算（MEC）系统是在没有通信资源基础设施的情况下进行计算卸载的有效解决方案。将可重构智能表面（RIS）引入无人机- mec系统可以提高空对地通信质量并优化非视距（N-LoS）链路。然而，如何根据环境变化动态选择RIS的业务用户，以减少信号干扰，提高资源利用率，仍然是一个需要解决的关键挑战。为了解决这一问题，我们的目标是共同优化无人机的三维（3D）轨迹，RIS选择决策和任务卸载策略，以最小化整个系统的延迟。由于关节问题的非凸性，传统的优化方法难以有效求解。为此，本文提出了一种基于深度强化学习（DRL）的混合探索深度确定性策略梯度（HEDDPG）算法。该算法将随机搜索集成到原始DDPG框架中，增强了复杂环境下的全局搜索能力。实验结果表明，加入RIS辅助后，系统延迟降低了18.8%。与其他基准算法相比，HEDDPG性能更好，实现了系统高效的策略优化，提高了通信链路性能和资源利用效率。

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引用次数: 0

A cooperative distributed model to evaluate and optimize task offloading in Mobile Edge Computing 移动边缘计算中任务卸载评估与优化的协作分布式模型

IF 4.3 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Computer Communications

Pub Date : 2025-12-20 DOI: 10.1016/j.comcom.2025.108403

Fabrizio Messina , Domenico Rosaci

This paper proposes a cooperative and distributed framework to evaluate and optimize task offloading in Mobile Edge Computing (MEC). Each agent, representing either a user device or an edge domain, autonomously interacts with others through trust-driven recommendations and cluster formation. The proposed algorithm exploits this information to iteratively increase – and asymptotically converge over time to – the configuration that maximizes the collective utility of edge servers and user devices, i.e., the Average Performance (

A P

), which corresponds to a Nash equilibrium where only reliable agents are rewarded. Two synthetic indicators are introduced to model the main aspects of MEC collaboration: the Quality of Experience (

Q o E

), representing the perceived user-side performance, and the Convenience (

C

), expressing the server-side efficiency and resource cost. Experimental validation, performed over a simulated MEC environment with up to 1000 agents, shows a rapid convergence (within 20 iterations), a stable equilibrium with

A P \approx 0.92

, and robustness to variations in the simulated values of agents’ reliability. The results demonstrate that the proposed distributed algorithm achieves efficient, self-organized coordination among heterogeneous edge entities while maintaining scalability and fairness.

提出了一种协作式分布式框架来评估和优化移动边缘计算（MEC）中的任务卸载。每个代理代表一个用户设备或一个边缘域，通过信任驱动的建议和集群形成自主地与其他代理交互。所提出的算法利用这些信息迭代地增加-并随着时间的推移渐近收敛-最大化边缘服务器和用户设备的集体效用的配置，即平均性能（AP），这对应于纳什均衡，其中只有可靠的代理得到奖励。引入了两个综合指标来对MEC协作的主要方面进行建模：体验质量（QoE），代表感知到的用户端性能，以及便利性(C)，表示服务器端效率和资源成本。在多达1000个代理的模拟MEC环境中进行的实验验证表明，该方法具有快速收敛（在20次迭代内）、稳定的平衡（AP≈0.92）以及对代理可靠性模拟值变化的鲁棒性。结果表明，该算法在保持可扩展性和公平性的同时，实现了异构边缘实体之间高效、自组织的协调。

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