IEEE Transactions on Green Communications and Networking最新文献

{"title":"Joint Transmit Beamforming and Phase Shift Design for RIS and NOMA Assisted Wireless Caching Systems With Non-Linear Energy Harvesting","authors":"Xuewei Zhang;Yapeng Zhang;Yuan Ren;Fan Jiang;Junxuan Wang;Jie Zeng","doi":"10.1109/TGCN.2026.3660741","DOIUrl":"https://doi.org/10.1109/TGCN.2026.3660741","url":null,"abstract":"This paper studies a new reconfigurable intelligent surface (RIS) aided wireless caching system. The RIS is equipped with a smart controller, and the functions of content caching and energy harvesting (EH) are endowed to the controller. We design a two-phase transmission policy. In the first phase, the requested contents that are not cached are delivered by the base station (BS) to RIS, and the controller conducts EH from surrounding radio frequency signals. In the second phase, the controller distributes cached contents utilizing non-orthogonal multiple access (NOMA) transmission with harvested energy, while the RIS forwards fetched contents sent from the BS to users. The beamforming vectors of the BS, RIS phase shifts, and NOMA power allocation factors are jointly optimized to maximize the achievable sum rate. The problem is intractable owing to coupled variables. After using the methods of fractional programming and quadratic transformation, we divide it into three sub-problems. The first sub-problem is solved by introducing auxiliary variables; the second one is addressed using the Riemannian manifold optimization; and the third one is converted to be convex by transforming the quality of service constraint. The sub-optimal solutions are achieved by alternatively solving the sub-problems. Simulation results reveal that the problem converges quickly, and the proposed algorithm outperforms benchmarks in terms of the sum rate.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"2107-2117"},"PeriodicalIF":6.7,"publicationDate":"2026-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175716","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":"Investigating the Potential of Kepler Toward Power Observability for Sustainable Cloud Computing","authors":"Zouhir Bellal;Laaziz Lahlou;Nadjia Kara;Timothy Murphy;Tan Phat Nguyen;Arif Ahmed;Mario Perez-Jimenez","doi":"10.1109/TGCN.2026.3660816","DOIUrl":"https://doi.org/10.1109/TGCN.2026.3660816","url":null,"abstract":"Power monitoring is a cornerstone of sustainability efforts, especially as the energy demands of Artificial Intelligence (AI) workloads continue to rise. However, accurately measuring power consumption in cloud-native environments remains challenging due to technical constraints such as fine-grained monitoring requirements and the high abstraction introduced by virtualization and containerization. Kepler (Kubernetes-based Efficient Power Level Exporter), an open-source tool for container-level power monitoring, has emerged as a promising solution for cloud power observability. This paper outlines the key requirements for accurate power tracking in containerized environments and assesses Kepler’s alignment with these criteria. However, its precision remains unvalidated, mainly due to the lack of a systematic evaluation methodology. To fill this gap, we introduce a novel accuracy validation framework tailored to assess container-level power monitoring tools under dynamic controlled multi-tenancy environments, including CPU frequency scaling, C-state transitions, and varying co-runner workloads (i.e., co-hosted containers executing concurrently on other cores of the same processor socket). Using this framework, we perform the first in-depth evaluation of Kepler’s accuracy in real-world cloud scenarios (e.g., dynamic power configuration settings, dynamic workloads). Our results show that Kepler’s container-level power estimation exhibits a root mean squared error (RMSE) of 11.9 Watts against the RAPL ground truth, corresponding to an overestimation of approximately <inline-formula> <tex-math>$15times $ </tex-math></inline-formula>. Its accuracy is highly sensitive to runtime factors such as CPU configuration and C-state transitions, which reveals critical limitations in Kepler’s current power model and highlights the need for refinement. This work establishes the foundation for more precise and effective power observability in cloud computing and paves the way for sustainable cloud computing.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"2118-2135"},"PeriodicalIF":6.7,"publicationDate":"2026-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146223796","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":"Composite Reward-Driven UGV Real-Time Data Acquisition With Green-Energy Supply","authors":"Minhan Qin;Jianhua Tang;Junyi Wang","doi":"10.1109/TGCN.2026.3659909","DOIUrl":"https://doi.org/10.1109/TGCN.2026.3659909","url":null,"abstract":"With the rapid growth of digital cities, massive sensing data distributed along road segments and roadside infrastructure need to be acquired and processed in a timely manner to support intelligent operations and infrastructure management. Owing to recent developments in unmanned ground vehicles (UGVs) technology and edge computing, UGVs can offload tasks to roadside units (RSUs), thereby greatly enhancing their data acquisition and processing capabilities. In this work, we consider both green-energy and grid-energy supplied RSUs. We deploy the UGV to traverse all target road segments in the considered road network, ensuring comprehensive acquisition of all data distributed along the roads. Furthermore, we introduce a composite reward to capture both the sustainability and time-sensitivity during data acquisition. Then, we establish a UGV reward collection problem that jointly optimizes UGV routing, speed control, task offloading ratios, and energy management. Considering the complexity of the problem, we propose an efficient iterative algorithm to solve it, in which an improved Branch-and-Bound algorithm is derived. Numerical experiments demonstrate that our approach outperforms baseline methods, while also effectively balancing timeliness and green-energy utilization.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"2052-2065"},"PeriodicalIF":6.7,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175659","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":"Intermittent Adaptive Resilient Secure Control for Nonlinear CPSs Under DoS Attacks in Sensor Networks","authors":"Xinjun Wang;Shenghang Liu;Xinyu Xu;Ben Niu;Huanqing Wang;Xudong Zhao","doi":"10.1109/TGCN.2026.3659499","DOIUrl":"https://doi.org/10.1109/TGCN.2026.3659499","url":null,"abstract":"This paper investigates the problem of adaptive prescribed-time intermittent resilient tracking control for a class of nonlinear cyber-physical systems (CPSs) under full-state denial-of-service (DoS) attacks with malicious intent. Since the disturbance of DoS attacks causes the discontinuity of the system states, which leads to its non-differentiability, it certainly increases the difficulty of the subsequent controller design. To overcome this obstacle, we reconstruct the system states by designing a set of adaptive high-gain observers, which generate differentiable state estimation signals. Subsequently, a time-varying constraint function is then integrated into the backstepping framework to construct a novel adaptive resilient controller with prescribed-time performance. This approach effectively converts the prescribed-time tracking control problem into a constraint problem for the tracking error. Meanwhile, a dynamic-threshold event-triggered mechanism (ETM) is proposed to minimize redundant signal transmissions and enhance the efficiency of network resource usage. Moreover, by using the Lyapunov stability theory, the proposed security control strategy ensures asymptotic convergence of the tracking error to zero, even in the absence of prior information regarding the frequency and duration of DoS attacks. Finally, the validity and practicality of the developed scheme are verified through simulation results on a one-link manipulator system.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"2066-2074"},"PeriodicalIF":6.7,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175715","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":"Sustainable Massive Connectivity Maximization Scheduling Scheme for 6G","authors":"Aamir Latif;Osama Elgarhy;Nurul Huda Mahmood;Yannick Le Moullec;Muhammad Mahtab Alam","doi":"10.1109/TGCN.2026.3659720","DOIUrl":"https://doi.org/10.1109/TGCN.2026.3659720","url":null,"abstract":"This paper proposes a scalable and energy-efficient scheduling framework tailored for massive machine-type communications (mMTC) in future 6G networks. Motivated by the dual challenges of massive connectivity and strict energy constraints, we introduce a new cooperative multi-cell uplink scheme that jointly optimizes user scheduling, power allocation, and interference management under finite block length (FBL) constraints. While prior studies have explored energy efficiency (EE) or connectivity separately, they often neglect FBL effects and lack scalable, interference-aware coordination across multi-cell NOMA deployments. Leveraging non-orthogonal multiple access (NOMA), our framework addresses both intra- and inter-cell interference through a multi-objective optimization problem that simultaneously maximizes EE and connectivity. To solve the problem, we develop the Sustainable and Reliable Scheduling for Massive Machine Type Communication using NOMA (SRS-MTCN) algorithm, integrating channel-aware user clustering, interference-aware resource allocation, and iterative power optimization. Simulation results demonstrate that the proposed approach performs significantly better than state-of-the-art baselines in dense deployments, achieving up to <inline-formula> <tex-math>$35-58%$ </tex-math></inline-formula> EE improvement in medium-density regimes (<inline-formula> <tex-math>$16 - 32$ </tex-math></inline-formula> devices/m2), while ensuring robust scalability and reliability in ultra-dense scenarios exceeding 40 devices/m2. These results illustrate its suitability for sustainable 6G mMTC networks operating under FBL and energy constraints.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"2075-2090"},"PeriodicalIF":6.7,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175928","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":"Decoding of LDPC Codes Using Singularity of SNR Mismatch Over AWGN Channel","authors":"Hong-Jae Jeong;Jae-Won Kim","doi":"10.1109/TGCN.2026.3659107","DOIUrl":"https://doi.org/10.1109/TGCN.2026.3659107","url":null,"abstract":"In this paper, we propose a new decoding algorithm that guarantees superior decoding performances for low-density parity-check (LDPC) codes without knowledge of channel parameters. Although obtaining correct channel parameters is very difficult in low-latency and energy-efficient communication systems, most studies on LDPC codes assume perfect knowledge of channel parameters. While receivers can obtain correct channel parameters by utilizing numerous pilot signals, increased overhead makes them infeasible in practical systems. In addition, using incorrect channel parameters for decoding usually degrades decoding performances. These challenges highlight the need for a new decoder that performs reliably without correct channel parameters. Meanwhile, the previous studies on repeat-accumulate (RA) codes and LDPC codes have observed that the signal-to-noise ratio (SNR) mismatch sometimes enhances decoding performances when the maximum number of decoding iterations is small. Inspired by these observations, we investigate singularity of the SNR mismatch in LDPC codes from numerous frame error rate (FER) simulations. By utilizing this singularity, we propose a new decoding algorithm for the energy-efficient communication system, where correct channel parameters are not available at receivers. The proposed decoder shows a performance gain of 0.25 dB at <inline-formula> <tex-math>$text {FER} = bf {10^{-6}}$ </tex-math></inline-formula> compared to the conventional belief propagation (BP) algorithm.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"2026-2036"},"PeriodicalIF":6.7,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175718","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":"Leader-Following Consensus for T-S Fuzzy Positive Multi-Agent Systems: A Model Prediction Control Approach","authors":"Haoyue Yang;Junfeng Zhang;Chongxiang Yu;Wei Xing","doi":"10.1109/TGCN.2026.3656314","DOIUrl":"https://doi.org/10.1109/TGCN.2026.3656314","url":null,"abstract":"This paper addresses the leader-following consensus problem for T-S fuzzy positive multi-agent systems using a model prediction control (MPC) approach. First, a positive multi-agent system model with a leader-follower structure is formulated via the T-S fuzzy modeling approach. Considering that the states of agents are not fully measurable, positive observers and distributed T-S fuzzy controllers are designed to achieve leader-following consensus. The main contributions of this work lie in the development of a novel MPC framework, which integrates a linear performance index, a co-positive Lyapunov function, and a linear programming solution technique. It has a simpler form and lower computational burden than existing methods based on quadratic indices and functions. Within this framework, an MPC algorithm is proposed to solve the min-max optimization problem associated with the performance index. Furthermore, the gain matrices for both the observer and the controller are systematically derived using a matrix decomposition technique. In view of a co-positive Lyapunov function, the positivity and consensus of the T-S fuzzy positive multi-agent system are rigorously proved under the proposed MPC strategy. Finally, an example is given to verify the effectiveness of the MPC design.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"1909-1921"},"PeriodicalIF":6.7,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146082232","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":"Intelligent Energy-Balancing Offloading and Routing for IoT in Collaborative GEO-LEO Satellite Networks","authors":"Meihui Li;Meng Li;Qi Li;Pengbo Si;Haijun Zhang;F. Richard Yu","doi":"10.1109/TGCN.2026.3655393","DOIUrl":"https://doi.org/10.1109/TGCN.2026.3655393","url":null,"abstract":"The emergence of Sixth Generation (6G) mobile communication technologies, along with the burgeoning proliferation of Internet of Things (IoT) devices, has significantly increased the requirements for computing resources. This growing demand places considerable pressure on the computing capacity. To address diverse and intensive application requirements, the integration of satellite and terrestrial networks is a key focus in the 6G vision. Within this context, the combination of a geostationary orbit (GEO) satellite and a low Earth orbit (LEO) satellite constellation is a crucial facilitator of IoT applications, addresses their computational demands while offering global coverage, low latency, seamless scalability, and strong reliability. However, several challenges arise in such networks: 1) LEO satellites are battery-powered and resource-constrained; 2) the number of LEO computing nodes is large and distributed; and 3) the network environment is highly dynamic and complex. To address these issues, a collaborative architecture for an LEO satellite constellation and a GEO satellite (CALG) is proposed. Based on the CALG, an energy-balancing strategy is designed to identify the optimal orbital plane for task offloading as well as an efficient routing path among satellites. The task offloading and routing selection are modeled by a Markov Decision Process, with a Proximal Policy Optimization (PPO) algorithm from deep reinforcement learning is applied to optimize decision-making in a dynamic environment. Experimental results demonstrate that the energy-balancing strategy based on PPO meets system performance requirements and outperforms baseline strategies.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"1841-1853"},"PeriodicalIF":6.7,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026525","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":"Separate Channel Estimation for RIS-Assisted Orbital Angular Momentum Communication Systems","authors":"Qibiao Zhu;Ting Tang;Jiantao Wang;Dejin Kong;Pei Liu;Ruiqi Liu","doi":"10.1109/TGCN.2026.3655689","DOIUrl":"https://doi.org/10.1109/TGCN.2026.3655689","url":null,"abstract":"For reconfigurable intelligence surface (RIS)-assisted orbital angular momentum (OAM) communication systems with alignment error, a separate channel estimation scheme for RIS-assisted OAM communication systems is proposed. Specifically, by employing a partial ON/OFF switching scheme, the channel parameters between the transmitter and the RIS can be directly estimated utilizing the linear minimum mean square error (LMMSE) estimator. Then, according to the dual relationship of the adjacent reflecting elements, the parameter matrix between the RIS and the receiver is estimated by the estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm, taking into account the received signal and the estimated channel parameters between the transmitter and the RIS. In addition, to alleviate the degradation of the achievable rate caused by the misalignment between the RIS and the receiver, a pre-receiving matrix is designed according to the estimated parameters. Subsequently, an alternating optimization (AO)-based Riemannian conjugate gradient (RCG) algorithm is presented to maximize the achievable rate. Simulation results demonstrate that the proposed scheme can accurately estimate the channel parameters, and the pre-receiving design and the AO-based RCG algorithm can significantly improve the achievable rate.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"2091-2106"},"PeriodicalIF":6.7,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175720","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":"Resource Allocation for RIS-Aided Cell-Free Massive MIMO-URLLC Network","authors":"Si-Nian Jin;Yiling Chen;Ziyi Tian;Jitong Ma;Dian-Wu Yue;Moran Ju","doi":"10.1109/TGCN.2026.3655209","DOIUrl":"https://doi.org/10.1109/TGCN.2026.3655209","url":null,"abstract":"Reconfigurable intelligent surface (RIS) have emerged as a transformative technology to enhance the performance of Internet-of-Things devices in service dead zones within cell-free massive multiple-input multiple-output (CFmMIMO) network, particularly in ultra-reliable and low-latency communication (URLLC) scenarios. Consequently, this paper investigates the rate performance of a RIS-aided CFmMIMO-URLLC network over Rician fading channel. First, we propose a low-overhead channel estimator and subsequently derive closed-form expressions for the downlink achievable rate under maximum ratio transmission (MRT) and zero-forcing (ZF) precoding schemes. According to these analytical expressions, we formulate a resource allocation problem aimed at maximizing the sum achievable rate by jointly optimizing the power control coefficient of base station and the phase shift of RIS. To tackle this non-convex problem, we propose an alternating optimization (AO) algorithm based on path-following method to approximate the complicated objective function as a logarithmic function. The resulting problem can be further decomposed into two subproblems, which are solved using an iterative optimization framework incorporating successive convex approximation and semidefinite relaxation techniques. Extensive numerical simulations validate the accuracy of the derived closed-form expressions and highlight the superior performance of ZF precoding in the short-packet regime. Finally, the proposed AO algorithm demonstrates significant improvements in rate performance for both MRT and ZF precoding schemes compared to several benchmark algorithms.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"1795-1810"},"PeriodicalIF":6.7,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026517","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}