IEEE Networking LettersPub Date : 2026-01-01Epub Date: 2026-02-18DOI: 10.1109/LNET.2026.3666045
Igor Bisio;Chiara Garibotto;Fabio Lavagetto;Andrea Sciarrone;Matteo Zerbino
{"title":"Optimized Resource Orchestration for CS-Enabled SHM in LoRa Networks","authors":"Igor Bisio;Chiara Garibotto;Fabio Lavagetto;Andrea Sciarrone;Matteo Zerbino","doi":"10.1109/LNET.2026.3666045","DOIUrl":"https://doi.org/10.1109/LNET.2026.3666045","url":null,"abstract":"The growing demand for sustainable monitoring solutions has positioned Wireless Sensor Networks (WSNs) and Low-Power Wide Area Networks (LPWANs) as critical enablers for Structural Health Monitoring (SHM). In this work, we propose a centralized optimization framework for LoRa-based IoT networks that jointly tunes the spreading factor, coding rate, and compression factor to balance energy efficiency and data reconstruction quality. A centralized controller dynamically adjusts communication parameters based on environmental conditions and application constraints. We evaluate system performance through extensive simulations under noisy channels. Results demonstrate the effectiveness of centralized orchestration in adapting to channel variability while minimizing the computational burden.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"8 ","pages":"258-262"},"PeriodicalIF":3.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11398120","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148442907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
IEEE Networking LettersPub Date : 2026-01-01Epub Date: 2026-03-11DOI: 10.1109/LNET.2026.3672779
Hui Chen;Xingyu Yuan;Chu-Fu Wang;He Li
{"title":"HSB-D2DStream: A Hybrid Semantic–Bit Communication Framework for Multi-User Live Video Streaming Over D2D Networks","authors":"Hui Chen;Xingyu Yuan;Chu-Fu Wang;He Li","doi":"10.1109/LNET.2026.3672779","DOIUrl":"https://doi.org/10.1109/LNET.2026.3672779","url":null,"abstract":"With the explosive growth of mobile video services and live streaming applications, future wireless networks face increasing pressure to deliver high-quality multimedia content under limited bandwidth and dynamic network conditions. Device-to-device (D2D) communication offers a promising solution by enabling direct content exchange among nearby users and alleviating backhaul congestion. However, existing D2D caching and streaming schemes often neglect the stringent delay, jitter, and throughput requirements inherent to video transmission, as well as the unique characteristics of semantic communication (SemCom), where meaning fidelity depends on knowledge matching between the transmitter and receiver. To address these challenges, this letter proposes HSB-D2DStream, a Hybrid Semantic–Bit D2D Streaming Algorithm for multi-user live video delivery in cache-enabled D2D networks. The base station (BS) selectively caches video chunks to a subset of users, which then disseminate content to others through optimized multi-hop D2D links. Each user dynamically selects between semantic and bit-level transmission modes based on its required video quality and background knowledge alignment. The proposed algorithm jointly optimizes user clustering, cache node selection, and D2D topology to maximize overall Quality of Service (QoS) while satisfying constraints on delay, jitter, and error rate.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"8 ","pages":"204-208"},"PeriodicalIF":3.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148493151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
IEEE Networking LettersPub Date : 2026-01-01Epub Date: 2026-03-19DOI: 10.1109/LNET.2026.3694836
Mahmoud Sami;Mohammed Atiquzzaman
{"title":"Execution-Time Valid Control for Dynamic LEO Satellite Networks","authors":"Mahmoud Sami;Mohammed Atiquzzaman","doi":"10.1109/LNET.2026.3694836","DOIUrl":"https://doi.org/10.1109/LNET.2026.3694836","url":null,"abstract":"Low Earth Orbit (LEO) satellite networks are a promising solution for global connectivity, Internet access, disaster management, and remote sensing applications. This letter defines execution-time feasibility under delayed and partially observed telemetry based on a telemetry-consistent belief set. We show that, under bounded state evolution and non-zero execution intervals, decision-time validation is insufficient. An execution-time feasibility framework is formulated that can adapt to existing control plane mechanisms in LEO satellite networks. The simulation results show that delay and uncertainty induce violations in the decision-time validation scheme, while the proposed execution-time feasibility framework certifies that network constraints remain satisfied throughout the execution interval.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"8 ","pages":"214-218"},"PeriodicalIF":3.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148493158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Low-Latency Post-Quantum Group Authentication Framework for VANETs","authors":"Ashutosh Kumar;Manik Malhotra;A. Anjali;Amrendra Singh Yadav","doi":"10.1109/LNET.2026.3666683","DOIUrl":"https://doi.org/10.1109/LNET.2026.3666683","url":null,"abstract":"Vehicular Ad Hoc Networks (VANETs) require ultra-low-latency authentication in high-mobility scenarios, decentralized trust, and emerging post-quantum security threats. This letter proposes a lightweight blockchain-assisted group authentication framework that integrates post-quantum cryptography with decentralized trust management. The scheme leverages CRYSTALS-Kyber for secure group key distribution, CRYSTALS-Dilithium for message authentication, and zero-knowledge proofs to achieve conditional anonymity and unlinkability. A permissioned Hyperledger Besu blockchain logs encrypted group keys and dynamically updated roadside unit reputation scores, enabling scalable and accountable authentication without monetary transaction overhead. Formal security analysis under the Dolev–Yao adversary model demonstrates confidentiality, authentication, replay resistance, and unlinkability based on standard post-quantum assumptions. Performance evaluation using OMNeT++ and SUMO shows up to 52.7% reduction in communication overhead and a group key update latency of 1.2 ms in dense traffic scenarios, while maintaining high throughput and effective Sybil attack detection. These results highlight the practicality of the proposed framework for post-quantum secure VANET authentication.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"8 ","pages":"125-129"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147665465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
IEEE Networking LettersPub Date : 2026-01-01Epub Date: 2026-06-24DOI: 10.1109/LNET.2026.3706755
Quan V. La;Junming Huang;Huy N. Le;Phuong Tran;Tung A. Nguyen;Phuong L. Vo;Bing B. Zhou;Nguyen H. Tran
{"title":"FORCE: Federated Orthogonality-Aware Low-Rank Adaptation for Communication-Efficient Fine-Tuning","authors":"Quan V. La;Junming Huang;Huy N. Le;Phuong Tran;Tung A. Nguyen;Phuong L. Vo;Bing B. Zhou;Nguyen H. Tran","doi":"10.1109/LNET.2026.3706755","DOIUrl":"https://doi.org/10.1109/LNET.2026.3706755","url":null,"abstract":"Federated fine-tuning of Large Language Models (LLMs) is fundamentally bottlenecked by the uplink communication capacity of edge networks. While Parameter-Efficient Fine-Tuning (PEFT) methods such as Low-Rank Adaptation (LoRA) reduce the payload by representing a dense <inline-formula> <tex-math>$dtimes k$ </tex-math></inline-formula> update with rank-<inline-formula> <tex-math>$r$ </tex-math></inline-formula> factors, they may suffer from subspace interference when aggregated across highly heterogeneous clients. In this letter, we propose <sc>FORCE</small>, a communication-efficient federated adaptation framework. Inspired by the philosophy of magnitude-direction decoupling, <sc>FORCE</small> introduces a local <italic>“project-and-compress”</i> geometric heuristic. Rather than transmitting dense orthogonal matrices, clients apply a lightweight 1-step gradient correction to align their low-rank updates toward an approximate orthonormal target before server aggregation, while preserving the <inline-formula> <tex-math>$mathcal {O}(r(d+k))$ </tex-math></inline-formula> low-rank communication budget. Empirical results demonstrate that <sc>FORCE</small> safely preserves model capacity in balanced networks and significantly mitigates performance degradation.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"8 ","pages":"325-328"},"PeriodicalIF":3.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148837131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"CVaR-Constrained Lyapunov Scheduling for Downlink Finite-Blocklength URLLC","authors":"Vitawat Sittakul;Iacovos Ioannou;Prabagarane Nagaradjane;Wai Yie Leong;Trong-Minh Hoang;Vasos Vassiliou","doi":"10.1109/LNET.2026.3711514","DOIUrl":"https://doi.org/10.1109/LNET.2026.3711514","url":null,"abstract":"Ultra-reliable low-latency communication (URLLC) requires short-packet transmission under stringent latency and reliability constraints, where rare delay excursions may dominate service failure. This letter investigates a risk-aware downlink scheduler for finite-blocklength (FBL) URLLC with random packet arrivals and block-error events. A Conditional Value-at-Risk (CVaR) constraint is embedded into Lyapunov drift-plus-penalty optimization by constructing a virtual tail-risk queue, which converts long-term tail-delay control into a queue-stability condition. The scheduler jointly determines transmit power and block length under per-slot power and channel-use constraints, and the resulting non-convex problem is handled via a convexified alternating procedure with a water-filling-like power update and projected block-length refinement. Simulations with 10 URLLC users show that the proposed policy reduces the average delay by about 23% and the empirical <inline-formula> <tex-math>$mathop {mathrm {CVaR}}nolimits _{0.99999}$ </tex-math></inline-formula> delay by 20–27% compared with a risk-neutral Lyapunov baseline, while maintaining bounded virtual backlog.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"8 ","pages":"334-338"},"PeriodicalIF":3.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148837134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
IEEE Networking LettersPub Date : 2026-01-01Epub Date: 2026-02-12DOI: 10.1109/LNET.2026.3664166
Juan Luis Herrera;Sofia Montebugnoli;Paolo Bellavista;Luca Foschini
{"title":"Management and Optimization of xApp and Near-Real-Time RIC Deployment in the Edge","authors":"Juan Luis Herrera;Sofia Montebugnoli;Paolo Bellavista;Luca Foschini","doi":"10.1109/LNET.2026.3664166","DOIUrl":"https://doi.org/10.1109/LNET.2026.3664166","url":null,"abstract":"O-RAN enables shared RAN Intelligent Controllers (RICs) hosting multiple xApps from different vendors, reducing operational costs. However, growing open-source RIC ecosystems face significant compatibility challenges, necessitating effective management of RIC deployment, xApp orchestration, and automated resource allocation strategies in the edge cloud continuum. We introduce MARRAS (Management and Allocation of Resources, RICs, and xAppS), a framework automating management and resource allocation in O-RAN environments. We formally define the underlying optimization problem and present a Mixed-Integer Linear Programming (MILP)-based solver. Results demonstrate MARRAS’s efficacy in enhancing O-RAN deployment operability and efficiency.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"8 ","pages":"130-134"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11395394","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147665369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"End-to-End Achievable Rate Maximized Resource Allocation in IRS-Aided IAB Network: A Multi-Agents DRL Framework-Based Scheme","authors":"Zhongyu Ma;Zhirong Liu;Jing Li;Guangjie Han;Qun Guo","doi":"10.1109/LNET.2026.3669091","DOIUrl":"https://doi.org/10.1109/LNET.2026.3669091","url":null,"abstract":"Intelligent reflecting surface (IRS) aided integrated access and backhaul (IAB) networks have emerged as a key technology for signal enhancement, coverage expansion and energy efficiency (EE) improvement in 6G systems. This correspondence investigates the resource allocation problem in IRS-aided IAB network. Firstly, the resource management including phase shift manipulation at IRS, transmission beamforming and bandwidth partition at IAB-node is formulated and decomposed into two sub-problems to maximize the system’s end-to-end achievable data rate. Secondly, the joint optimization scheme of improved multi-agent deep deterministic policy gradient (MADDPG) combining block coordinate descent (BCD) is proposed, where the IRS phase shift is optimized through the BCD approach, the optimal transmission beamforming and bandwidth partition are dynamically adjusted through the MADDPG. Finally, the proposed scheme performance is evaluated through diversified experimental simulation scenarios in terms of convergence and effectiveness including system EE and end-to-end achievable rate.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"8 ","pages":"184-188"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147665524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Audio Physical Dynamics Inspired Deepfake Detection for Voice Authentication Systems","authors":"Alireza Mohammadi;Keshav Sood;Dhananjay Thiruvady;Asef Nazari","doi":"10.1109/LNET.2026.3725616","DOIUrl":"https://doi.org/10.1109/LNET.2026.3725616","url":null,"abstract":"Voice authentication systems deployed at the network edge face dual threats: a) sophisticated deepfake synthesis attacks and b) control-plane poisoning in distributed federated learning protocols. We present a framework coupling audio physical dynamics deepfake detection with uncertainty-aware in edge learning. The framework fuses interpretable physics features modeling vocal tract dynamics with representations coming from a self-supervised learning module. The representations are then processed via a streamlined Multi-Layer Perceptron backbone, followed by a Bayesian ensemble providing uncertainty estimates. Incorporating audio physical characteristics evaluations and uncertainty estimates of audio samples allows our proposed framework to remain robust to advanced deepfake attacks, while our trust-based aggregation protocol secures the control plane against poisoning in network edge voice authentication systems.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"8 ","pages":"349-353"},"PeriodicalIF":3.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148837277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
IEEE Networking LettersPub Date : 2026-01-01Epub Date: 2026-06-18DOI: 10.1109/LNET.2026.3705053
Yujie Qin;Mustafa A. Kishk;Ahmed Elzanaty;Luca Chiaraviglio;Mohamed-Slim Alouini
{"title":"Performance Analysis of User Altitude Influence on the EMF Exposure From Earth Station to Satellite Communications","authors":"Yujie Qin;Mustafa A. Kishk;Ahmed Elzanaty;Luca Chiaraviglio;Mohamed-Slim Alouini","doi":"10.1109/LNET.2026.3705053","DOIUrl":"https://doi.org/10.1109/LNET.2026.3705053","url":null,"abstract":"Integrating satellites into current communication networks is expected to bridge the digital divide. However, when Earth stations (or ground stations) communicate with nearby satellites, they generate significant power, leading to potential electromagnetic field (EMF) exposure for nearby humans: humans may experience either mainlobe or sidelobe exposure from the feeder link of Earth stations, which depends on user altitudes and the satellite positions. To analyze the EMF exposure from feeder link of Earth stations to satellites, we utilize tools from stochastic geometry to model the locations of the Earth stations and satellites, and capture the impact of user altitude on the EMF exposure. Initially, we analyze the angle between the user and the mainlobe from the antenna array of Earth stations, which corresponds to the angle between satellites and users. Subsequently, we compute the mean exposure index (EI), a commonly used performance metric in EMF exposure analysis, as well as the percentiles of the EI. Our numerical results demonstrate that increasing user altitude generally reduces the mean EI due to weaker alignment with Earth-station mainlobes, while percentile analysis reveals that high-exposure events may still occur under dense satellite deployments.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"8 ","pages":"358-362"},"PeriodicalIF":3.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148836905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}