IEEE Transactions on Green Communications and Networking最新文献

{"title":"Optimizing Energy Efficiency for Federated Learning in Rotary-Wing UAV Air-to-Ground Communications","authors":"Xuan-Toan Dang;Quynh-Suong Nguyen;Oh-Soon Shin","doi":"10.1109/TGCN.2025.3599309","DOIUrl":"https://doi.org/10.1109/TGCN.2025.3599309","url":null,"abstract":"In the 5G and upcoming 6G eras, federated learning (FL) plays a crucial role in enabling intelligent, privacy-preserving networks by training models locally on user devices. However, FL faces challenges such as unstable wireless channels and limited device energy. This paper proposes a UAV-assisted framework to reduce energy consumption in FL by allowing simultaneous user transmissions over shared spectrum. We consider realistic air-to-ground (A2G) communication, including both LoS and NLoS links between the UAV and UEs, while accounting for the UAV’s limited energy. The problem of minimizing user energy consumption during FL is formulated as a nonconvex optimization, which is efficiently solved using alternating optimization and inner approximation techniques. Simulation results demonstrate the effectiveness of our approach in optimizing UAV placement and improving energy efficiency.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"829-843"},"PeriodicalIF":6.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148509986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optical RIS-Enabled Multiple Access Communications","authors":"Georgios D. Chondrogiannis;Athanasios P. Chrysologou;Alexandros-Apostolos A. Boulogeorgos;Nestor D. Chatzidiamantis;Harald Haas","doi":"10.1109/TGCN.2025.3609409","DOIUrl":"https://doi.org/10.1109/TGCN.2025.3609409","url":null,"abstract":"In this paper, we identify optical reconfigurable intelligent surfaces (ORISs) as key enablers of next-generation free-space optical (FSO) multiple access systems. By leveraging their beam steering and beam splitting capabilities, ORISs are able to effectively address line-of-sight (LoS) constraints, while enabling multi-user connectivity. We consider an ORIS-assisted non-orthogonal multiple access (NOMA) system model consisting of a single transmitter (Tx) and two receivers (Rxs). We derive novel analytical expressions to characterize the statistical particularities of the Tx-ORIS-Rx communication channel. Building upon the aforementioned expressions, we investigate the outage performance of the Rxs by deriving exact analytical expressions for the outage probability (OP) of each Rx. To provide deeper insights into the impact of various system parameters and physical conditions on the outage performance of each Rx, we conduct a high signal-to-noise ratio (SNR) analysis, that returns asymptotic expressions for the Rx OPs at the high-SNR regime. Monte Carlo simulations validate the analysis, demonstrate the effectiveness of ORIS-enabled NOMA under a variety of configurations and physical scenarios, and showcase its superiority over its orthogonal-based counterpart.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"1068-1080"},"PeriodicalIF":6.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148510470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Full-Space UAV Trajectory Design for STAR-RIS-Assisted Secure Ground–Air Communications","authors":"Xiangyun Meng;Xuanli Wu","doi":"10.1109/TGCN.2025.3581390","DOIUrl":"https://doi.org/10.1109/TGCN.2025.3581390","url":null,"abstract":"In this paper, we study simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-assisted secure ground-air communications. Ground nodes upload data to an unmanned aerial vehicle (UAV) with the assistance of a STAR-RIS, while facing eavesdropping threats targeting confidential information from a secure node. Planning UAV trajectories in a full space instead of only on the single side of a STAR-RIS is helpful to make the most of UAV flexibility. However, the transmission rates of ground nodes is hard to express because cascaded channels vary with the UAV’s location relative to the STAR-RIS. To address this issue, we propose a unified expression of the rate incorporating the UAV-location-dependent cascaded channels. Based on the proposed expression, we maximize the average secrecy rate (ASR) of a secure node while ensuring the rate requirements of a regular node via robust optimization of STAR-RIS coefficients and UAV trajectory. Specifically, we consider the imperfect eavesdropping channel state information. Due to the non-convex structure, the original mixed integer nonlinear programming problem is decomposed into two subproblems. Semidefinite relaxation, <inline-formula> <tex-math>$mathcal {S}$ </tex-math></inline-formula>-Procedure, and successive convex approximation techniques are used to tackle the non-convex objective function and constraints. Finally, the two subproblems are solved iteratively. Numerical simulations reveal that the proposed scheme achieves the full-space flight of the UAV and outperforms the benchmark schemes in terms of ASR.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"376-388"},"PeriodicalIF":6.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148510878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy-Efficient 5G Integrated Access and Backhaul Open RAN-Based Fixed Wireless Access Provisioning in Rural Areas","authors":"Anselme Ndikumana;Kim Khoa Nguyen;Mohamed Cheriet","doi":"10.1109/TGCN.2025.3647528","DOIUrl":"https://doi.org/10.1109/TGCN.2025.3647528","url":null,"abstract":"Fixed Wireless Access (FWA) has emerged as a promising solution for providing Internet access to rural areas where fiber deployment is not economically feasible. Recently, 5G-based FWA has been demonstrated to offer high coverage and capacity using mid and high-frequency bands. However, these bands require more radio units to increase capacity and coverage. Additionally, 5G-based FWA necessitates the deployment of edge clouds for proximity computation and hosting network functions. However, deploying more radios and leveraging edge cloud infrastructure can increase the network’s energy consumption. Therefore, such 5G-based FWA should be designed and powered by renewable energy to be sustainable and cost-efficient in rural areas. To address these challenges, we propose energy-efficient 5G Integrated Access and Backhaul Open Radio Access Network-based FWA (5G IAB and Open RAN-based FWA) serving rural areas, where Open RAN supports the interoperability of 5G-based FWA elements. We design an energy model that leverages the power grid and renewable energy to serve IAB and Open RAN-based FWA. We join the communication model with the energy model. Then, we formulate a joint optimization problem to minimize energy consumption while maximizing communication utility. We propose concave programming and disciplined convex programming as solutions. The results show that our approach can increase network and energy utility by leveraging renewable energy.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"1642-1653"},"PeriodicalIF":6.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148511368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hybrid Sensitivity and Residual Subspace Refinement-Based Scheduling in Massive IoT","authors":"Shao-Di Wang;Chang-Long Wang;Jun Sun;Feng Zhou;Victor C. M. Leung","doi":"10.1109/TGCN.2026.3721971","DOIUrl":"https://doi.org/10.1109/TGCN.2026.3721971","url":null,"abstract":"With the exponential increase in Internet of Things (IoT) deployments, advanced resource scheduling is needed to address massive connectivity and strict quality of service requirements. In this paper, we propose a hybrid sensitivity and residual subspace refinement (HSRSR) method for protocol-aware coordination between uplink control information reporting and downlink control information scheduling. HSRSR integrates sensitivity driven subspace selection for feedback compression and residual based subspace determination for dynamic scheduling. Sensitivity analysis extracts dominant eigenmodes from channel covariance matrices to preserve mutual information for modulation and coding scheme adaptation. Residual based prioritization adapts resource block group allocations and beamforming by selecting active constraints according to their Lagrange multiplier magnitudes. Compared with codebook based scheduling and heuristic interference coordination based scheduling, HSRSR achieves a sum rate gain of up to 46% under moderate delay constraints with a channel quality indicator quantization granularity of zero point one bits per hertz. Additionally, HSRSR reduces computational complexity from cubic to linear scaling with the number of devices, enabling real-time scheduling in massive IoT networks. Furthermore, it outperforms these baselines while maintaining protocol-compliant resource allocation.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"3915-3928"},"PeriodicalIF":6.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148747501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the Performance of Low-Complexity Decoders of LDPC Codes","authors":"Qingqing Peng;Dawei Yin;Dongxu Chang;Yuan Li;Huazi Zhang;Guiying Yan;Guanghui Wang","doi":"10.1109/TGCN.2026.3718068","DOIUrl":"https://doi.org/10.1109/TGCN.2026.3718068","url":null,"abstract":"Efficient decoding is crucial to high-throughput and power-sensitive wireless communication scenarios. A theoretical analysis of the performance-complexity tradeoff toward low-complexity decoding is required for a better understanding of the fundamental limits in the above-mentioned scenarios. This study aims to explore the performance of LDPC codes under belief propagation (BP) decoding with complexity constraints. In other words, for a small number of iterations, we present a closed-form lower bound on the bit error rate (BER) of LDPC codes as a function of complexity. Specifically, for the regular LDPC code ensembles, the dominant term in the order of the lower bound we provide matches that of the upper bound given by Lentmaier. Furthermore, for irregular LDPC code ensembles, in addition to adopting the approach used for regular codes, we also propose a method to iteratively obtain the lower bound on the average BER.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"3856-3870"},"PeriodicalIF":6.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148747513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Green Emergency Communications in RIS- and MA-Assisted Multi-UAV SAGINs: A Partially Observable Reinforcement Learning Approach","authors":"Liangshun Wu;Wen Chen;Shunqing Zhang;Yajun Wang;Kunlun Wang","doi":"10.1109/TGCN.2026.3716272","DOIUrl":"https://doi.org/10.1109/TGCN.2026.3716272","url":null,"abstract":"In post-disaster space–air–ground integrated networks (SAGINs), terrestrial infrastructure is often impaired, and unmanned aerial vehicles (UAVs) must rapidly restore connectivity for mission-critical ground terminals in cluttered non-line-of-sight (NLoS) urban environments. To enhance coverage, UAVs employ movable antennas (MAs), while reconfigurable intelligent surfaces (RISs) on surviving high-rise buildings redirect signals. The key challenge is communication-limited partial observability, leaving each UAV with a narrow, fast-changing neighborhood view that destabilizes value estimation. Existing multi-agent reinforcement learning (MARL) approaches are inadequate, in that non-communication methods rely on unavailable global critics, heuristic sharing is brittle and redundant, and learnable protocols (e.g., CommNet, DIAL) lose per-neighbor structure and aggravate non-stationarity under tight bandwidth. To address partial observability, we propose a spatiotemporal A2C where each UAV transmits prior-decision messages with local state, a compact policy fingerprint, and a recurrent belief, encoded per neighbor and concatenated. A spatial discount shapes value targets to emphasize local interactions, while analysis under one-hop-per-slot latency explains stable training with delayed views. Experimental results show our policy outperforms IA2C, ConseNet, FPrint, DIAL, and CommNet, achieving faster convergence, higher asymptotic reward, reduced temporal-difference(TD), advantage estimation errors, and a better communication throughput–energy trade-off.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"3742-3755"},"PeriodicalIF":6.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148748040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Joint Precoding and Reflective Beamforming for RIS-Assisted ISCC Networks: A Cross-Layer Optimization Approach","authors":"Yingsheng Peng;Jinbei Zhang;Jingpu Duan;Weichao Li;Yong Liu","doi":"10.1109/TGCN.2026.3717710","DOIUrl":"https://doi.org/10.1109/TGCN.2026.3717710","url":null,"abstract":"Integrated sensing, communication, and computing (ISCC) technology significantly improves spectrum efficiency and reduces hardware costs by unifying the functionalities of sensing, communication, and computation. However, the degradation of wireless link quality caused by obstacles may lead to severe offloading latency. This paper investigates the application of reconfigurable intelligent surface (RIS) technology in ISCC network to enhance the reliability of wireless links and improve the efficiency of computation offloading. In the proposed network, integrated sensing and communication (ISAC) devices employ the same hardware and signaling mechanisms to perform both sensing and communication tasks, while mobile edge computing (MEC) technology is leveraged to process sensing data. To address the cross-layer resource management problem, we formulate a total latency minimization problem for both communication and computation under sensing accuracy constraints, by jointly optimizing the waveform precoding design matrix of ISAC devices, the beam pattern scaling factor, the RIS’s reflective beamforming, and the computing frequency of edge server (ES). Since this problem is highly non-convex, we propose an iterative algorithm based on block coordinate descent (BCD) framework, which leverages semi-definite relaxation (SDR) method, the Charnes-Cooper transform (CCT) method, and closed-form solution to alternately optimize three variable blocks until convergence is achieved for the final solution. Extensive simulations validate the effectiveness of the proposed scheme, demonstrating that the RIS-assisted joint optimization scheme significantly reduces the total system latency. Moreover, we reveal the trade-off between sensing accuracy and system latency.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"3929-3940"},"PeriodicalIF":6.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148750130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GreenAuth: Risk-Adaptive Cryptographic Authentication for Scalable and Energy-Efficient 6G-IoT Networks","authors":"Hasan Bulut;Sevtap Duman","doi":"10.1109/TGCN.2026.3719259","DOIUrl":"https://doi.org/10.1109/TGCN.2026.3719259","url":null,"abstract":"IMT-2030/6G aims for ultra-dense connectivity, making always-on, per-message authentication a scalability and energy bottleneck. Digital signatures offer strong authenticity and non-repudiation but impose high signing and verification costs on battery-powered IoT nodes and edge verifiers, while MACs are much cheaper but their security degrades significantly if symmetric keys are compromised.We propose GreenAuth, a risk-adaptive authentication framework that uses MACs by default and escalates to digital signatures for: 1) application-defined critical messages (fraction <inline-formula> <tex-math>$phi $ </tex-math></inline-formula>); and 2) a bounded post-alert signing window of duration <inline-formula> <tex-math>$tau _{w}$ </tex-math></inline-formula> triggered by an anomaly detector. We develop a unified model that captures authentication-related compute energy, communication overhead, and edge verification latency using both M/M/<inline-formula> <tex-math>$c$ </tex-math></inline-formula> and deterministic-service (M/D/<inline-formula> <tex-math>$c$ </tex-math></inline-formula>) queueing abstractions, and validate it with a reproducible discrete-event simulator at scales up to <inline-formula> <tex-math>$10{,}000$ </tex-math></inline-formula> devices. Across four hardware profiles—including a post-quantum Dilithium-2 setting—GreenAuth preserves signature protection for all critical traffic while reducing authentication energy to approximately 10% of always-sign, revealing an explicit <inline-formula> <tex-math>$(phi,tau _{w})$ </tex-math></inline-formula> energy–security trade-off surface that supports operator-driven configuration.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"3815-3827"},"PeriodicalIF":6.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148748159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Latency-Aware Residual DRL for Energy-Efficient Multi-RIS Assisted High-Speed Railway Communications","authors":"Hai-Nam Le;Hoang Trong Minh;Lam Sinh Cong;Xuan Nam Tran;Pham Thanh Hiep","doi":"10.1109/TGCN.2026.3728644","DOIUrl":"https://doi.org/10.1109/TGCN.2026.3728644","url":null,"abstract":"Maximizing energy efficiency in multiple Reconfigurable Intelligent Surface (RIS)-assisted High-Speed Railway (HSR) networks presents a formidable challenge due to the coupled dynamics of high-mobility Doppler effects, strict latency constraints, and the necessity for joint transmit power and beamforming control. Existing optimization approaches, such as genetic algorithms (GA) and Continuous relaxation methods, often suffer from limited practical effectiveness due to high computational latency, leading to beam aging–a critical misalignment between the optimized beam and the fast-moving train. Furthermore, these methods typically rely on fixed power allocation or saturated optimization strategies that fail to adapt to rapid channel fluctuations. To address these issues, we propose a novel Latency-aware Residual Twin Delayed Deep Deterministic Policy Gradient (TD3) Deep Reinforcement Learning (DRL) framework. Unlike standard opaque DRL, our agent integrates: 1) a clamped residual learning architecture that jointly fine-tunes geometric beamforming and transmit power; and 2) a zero-initialization strategy to eliminate unstable warm-up phases. We evaluate this framework under a 3GPP TR 38.901-compliant high-mobility channel model with spatially consistent, per-path Doppler generation and delay-affected channel state information, benchmarking against classical (Dinkelbach-SLSQP) and metaheuristic (GA) solvers as well as a predictive extended Kalman filter-based tracking baseline that isolates the benefit of latency prediction from that of learning-based control. Comprehensive Monte Carlo simulations, including a ±15% time-varying velocity profile that stress-tests robustness to both random fading and kinematic uncertainty, show that the proposed DRL agent consistently achieves the lowest optimality gap and the tightest confidence intervals of all methods, particularly at ultra-high speeds (500 km/h) with large-scale RIS arrays, through a power allocation strategy that intelligently backs off power under favorable channel conditions to maximize efficiency.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"4174-4189"},"PeriodicalIF":6.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148925734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}