Pub Date : 2025-12-11DOI: 10.1109/TGCN.2025.3642402
Fangli Yang;Liang Chang;Daowen Qiu;Minghua Pan
Free-space quantum cryptography holds significant potential for enabling global quantum communication networks. This paper proposes a free-space continuous-variable quantum secret sharing (CV-QSS) protocol employing a local local oscillator (LLO). The proposed protocol simplifies the system architecture by requiring only two heterodyne detections at the dealer’s side, thereby eliminating the additional noise and complexity associated with coherent measurements at each participant’s side in conventional schemes. Theoretically, we establish a channel transmittance model that comprehensively incorporates the effects of rain extinction and atmospheric turbulence, and derive the bound of the secret key rate. Experimentally, we systematically evaluate the impact of weather conditions and atmospheric turbulence on protocol performance and conduct comparative evaluations against existing schemes. The results demonstrate that the proposed protocol outperforms the previously proposed free-space LLO-based CV-QSS protocol in terms of key rate, transmission distance, noise tolerance, and participant capacity. Furthermore, this protocol supports secret sharing among 5 participants over 75 km or up to 37 participants within 10 km, outperforming the LLO-based CV-QSS system in a fiber channel. This study validates the potential of free-space CV-QSS as a viable solution for medium-to-long-distance and multi-user quantum secret sharing.
{"title":"Free-Space Continuous-Variable Quantum Secret Sharing","authors":"Fangli Yang;Liang Chang;Daowen Qiu;Minghua Pan","doi":"10.1109/TGCN.2025.3642402","DOIUrl":"https://doi.org/10.1109/TGCN.2025.3642402","url":null,"abstract":"Free-space quantum cryptography holds significant potential for enabling global quantum communication networks. This paper proposes a free-space continuous-variable quantum secret sharing (CV-QSS) protocol employing a local local oscillator (LLO). The proposed protocol simplifies the system architecture by requiring only two heterodyne detections at the dealer’s side, thereby eliminating the additional noise and complexity associated with coherent measurements at each participant’s side in conventional schemes. Theoretically, we establish a channel transmittance model that comprehensively incorporates the effects of rain extinction and atmospheric turbulence, and derive the bound of the secret key rate. Experimentally, we systematically evaluate the impact of weather conditions and atmospheric turbulence on protocol performance and conduct comparative evaluations against existing schemes. The results demonstrate that the proposed protocol outperforms the previously proposed free-space LLO-based CV-QSS protocol in terms of key rate, transmission distance, noise tolerance, and participant capacity. Furthermore, this protocol supports secret sharing among 5 participants over 75 km or up to 37 participants within 10 km, outperforming the LLO-based CV-QSS system in a fiber channel. This study validates the potential of free-space CV-QSS as a viable solution for medium-to-long-distance and multi-user quantum secret sharing.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"1578-1590"},"PeriodicalIF":6.7,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830873","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}
Pub Date : 2025-12-10DOI: 10.1109/TGCN.2025.3642525
{"title":"2025 Index IEEE Transactions on Green Communications and Networking","authors":"","doi":"10.1109/TGCN.2025.3642525","DOIUrl":"https://doi.org/10.1109/TGCN.2025.3642525","url":null,"abstract":"","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 4","pages":"1-41"},"PeriodicalIF":6.7,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11296750","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145729360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-10DOI: 10.1109/TGCN.2025.3642779
Matias Romário Pinheiro Dos Santos;Rodrigo Izidoro Tinini;Gustavo Bittencourt Figueiredo
Cloud Radio Access Network (CRAN) has become a popular approach for migrating Baseband Units (BBUs) to the cloud using Network Functions Virtualization (NFV). However, bandwidth and latency constraints are significant challenges for CRAN deployment. To address these limitations, Cloud-Fog RAN (CF-RAN) has been proposed as an alternative solution. In this paper, we consider a cutting-edge CF-RAN scenario with different functional-split choices of virtualized BBUs with varying bandwidth and latency constraints. We propose an Integer Linear Programming (ILP) model to optimize functional split and allocate resources for optimal virtualized BBU placement, with the objective of minimizing power consumption. Our approach includes a novel queuing delay model based on the eCPRI standard. We also introduce a heuristic to address scalability issues. Dynamic simulations show that our method improves network availability by 35% and optimizes power consumption by 9.93%, outperforming prior studies. Our findings contribute to developing efficient CF-RAN systems and demonstrate the effectiveness of our proposed approach.
云无线接入网（CRAN）已经成为使用网络功能虚拟化（NFV）将基带单元（BBUs）迁移到云的流行方法。然而，带宽和延迟限制是CRAN部署面临的重大挑战。为了解决这些限制，Cloud-Fog RAN （CF-RAN）被提出作为一种替代解决方案。在本文中，我们考虑了一个前沿的CF-RAN场景，该场景具有不同带宽和延迟约束的虚拟化bbu的不同功能拆分选择。我们提出了一个整数线性规划（ILP）模型来优化功能分裂和分配资源，以实现最佳的虚拟化BBU放置，目标是最小化功耗。我们的方法包括一个新的基于eCPRI标准的排队延迟模型。我们还引入了一个启发式方法来解决可伸缩性问题。动态仿真结果表明，该方法提高了35%的网络可用性，优化了9.93%的功耗，优于以往的研究。我们的发现有助于开发高效的CF-RAN系统，并证明了我们提出的方法的有效性。
{"title":"Energy-Efficient Flexible Functional Splitting in Latency-Constrained O-RAN","authors":"Matias Romário Pinheiro Dos Santos;Rodrigo Izidoro Tinini;Gustavo Bittencourt Figueiredo","doi":"10.1109/TGCN.2025.3642779","DOIUrl":"https://doi.org/10.1109/TGCN.2025.3642779","url":null,"abstract":"Cloud Radio Access Network (CRAN) has become a popular approach for migrating Baseband Units (BBUs) to the cloud using Network Functions Virtualization (NFV). However, bandwidth and latency constraints are significant challenges for CRAN deployment. To address these limitations, Cloud-Fog RAN (CF-RAN) has been proposed as an alternative solution. In this paper, we consider a cutting-edge CF-RAN scenario with different functional-split choices of virtualized BBUs with varying bandwidth and latency constraints. We propose an Integer Linear Programming (ILP) model to optimize functional split and allocate resources for optimal virtualized BBU placement, with the objective of minimizing power consumption. Our approach includes a novel queuing delay model based on the eCPRI standard. We also introduce a heuristic to address scalability issues. Dynamic simulations show that our method improves network availability by 35% and optimizes power consumption by 9.93%, outperforming prior studies. Our findings contribute to developing efficient CF-RAN systems and demonstrate the effectiveness of our proposed approach.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"1538-1551"},"PeriodicalIF":6.7,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11296907","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-09DOI: 10.1109/TGCN.2025.3642128
Zhaotao Zhang;Xiaohan Li;Xinjiang Xia;Chenfei Fan;Pengcheng Zhu;Dongming Wang;Tiecheng Song
The traditional massive multiple-input multiple-output (MIMO) system faces spectral efficiency limitations due to half-duplex constraints and centralized processing bottlenecks. This paper proposes a network-assisted free duplex (NA-FD) architecture in a cell-free radio access network (CF-RAN) system. In this architecture, user equipments (UEs) operate in half-duplex mode, while access points (APs) can support both full-duplex and half-duplex modes, significantly reducing inter-link interference. The distributed framework features edge distributed units (EDUs) that handle both uplink (demodulating signals for central processing unit (CPU) to aggregate) and downlink (precoding data for AP to transmit) processing, reducing backhaul load and enhancing scalability. For CF-RAN NA-FD, the following three works synergistically to improve system spectral efficiency and reduce computational overhead by optimizing the distributed association: 1) discrete differential evolution (DDE)-based EDU-AP association, 2) evolutionary and coalition game-theoretic AP mode selection, 3) experience replay (ER)-enhanced distributed Q-learning for capacity-constrained EDU-UE association. Simulation results demonstrate the effectiveness of our proposed architecture in achieving efficient resource allocation, significantly improving system performance and user quality of service.
{"title":"Duplex Mode Selection and Distributed Association for Cell-Free RAN With Network-Assisted Free Duplex","authors":"Zhaotao Zhang;Xiaohan Li;Xinjiang Xia;Chenfei Fan;Pengcheng Zhu;Dongming Wang;Tiecheng Song","doi":"10.1109/TGCN.2025.3642128","DOIUrl":"https://doi.org/10.1109/TGCN.2025.3642128","url":null,"abstract":"The traditional massive multiple-input multiple-output (MIMO) system faces spectral efficiency limitations due to half-duplex constraints and centralized processing bottlenecks. This paper proposes a network-assisted free duplex (NA-FD) architecture in a cell-free radio access network (CF-RAN) system. In this architecture, user equipments (UEs) operate in half-duplex mode, while access points (APs) can support both full-duplex and half-duplex modes, significantly reducing inter-link interference. The distributed framework features edge distributed units (EDUs) that handle both uplink (demodulating signals for central processing unit (CPU) to aggregate) and downlink (precoding data for AP to transmit) processing, reducing backhaul load and enhancing scalability. For CF-RAN NA-FD, the following three works synergistically to improve system spectral efficiency and reduce computational overhead by optimizing the distributed association: 1) discrete differential evolution (DDE)-based EDU-AP association, 2) evolutionary and coalition game-theoretic AP mode selection, 3) experience replay (ER)-enhanced distributed Q-learning for capacity-constrained EDU-UE association. Simulation results demonstrate the effectiveness of our proposed architecture in achieving efficient resource allocation, significantly improving system performance and user quality of service.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"1603-1617"},"PeriodicalIF":6.7,"publicationDate":"2025-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830872","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}
Pub Date : 2025-12-08DOI: 10.1109/TGCN.2025.3641183
Afan Ali;Abdelali Arous;Hüseyin Arslan
The high Peak-to-average-power ratio (PAPR) is still a common issue in multicarrier signal modulation systems such as Orthogonal Chirp Division Multiplexing (OCDM) and Affine Frequency Division Multiplexing (AFDM), which are expected to play a central role in 6G networks. This paper presents a novel unified premodulation data spreading framework that repurposes four well-established transforms—Walsh-Hadamard Transform (WHT), Discrete Cosine Transform (DCT), Zadoff-Chu (ZC) sequences, and Interleaved Discrete Fourier Transform (IDFT)—to achieve up to 4 dB PAPR reduction with lower complexity and zero side information. Conventional PAPR reduction frameworks such as Partial transmission Sequence (PTS) or Selected Mapping (SLM) have a high complexity drawback, as they require extensive search and signaling overhead. In contrast, our framework leverages fast transforms and the inherent chirp structure to redistribute energy before modulation without additional overhead, delivering not only superior PAPR performance but also enhanced phase selectivity and interference resilience. Extensive simulations and analytical derivations confirm its energy efficiency and scalability in large-scale IoT deployments.
{"title":"Spreading the Wave: Low-Complexity PAPR Reduction for AFDM and OCDM in 6G Networks","authors":"Afan Ali;Abdelali Arous;Hüseyin Arslan","doi":"10.1109/TGCN.2025.3641183","DOIUrl":"https://doi.org/10.1109/TGCN.2025.3641183","url":null,"abstract":"The high Peak-to-average-power ratio (PAPR) is still a common issue in multicarrier signal modulation systems such as Orthogonal Chirp Division Multiplexing (OCDM) and Affine Frequency Division Multiplexing (AFDM), which are expected to play a central role in 6G networks. This paper presents a novel unified premodulation data spreading framework that repurposes four well-established transforms—Walsh-Hadamard Transform (WHT), Discrete Cosine Transform (DCT), Zadoff-Chu (ZC) sequences, and Interleaved Discrete Fourier Transform (IDFT)—to achieve up to 4 dB PAPR reduction with lower complexity and zero side information. Conventional PAPR reduction frameworks such as Partial transmission Sequence (PTS) or Selected Mapping (SLM) have a high complexity drawback, as they require extensive search and signaling overhead. In contrast, our framework leverages fast transforms and the inherent chirp structure to redistribute energy before modulation without additional overhead, delivering not only superior PAPR performance but also enhanced phase selectivity and interference resilience. Extensive simulations and analytical derivations confirm its energy efficiency and scalability in large-scale IoT deployments.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"1565-1577"},"PeriodicalIF":6.7,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830940","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}
This paper proposes a novel OTFS (orthogonal time frequency space)-based MIMO Integrated Sensing and Communication (ISAC) system that achieves real-time channel reconstruction through advanced target parameter estimation. However, existing OTFS techniques still encounter challenges in sensing performance when applied to scenarios characterized by fractional delays and fractional Doppler frequency shifts. A novel radar channel matrix model in the delay-Doppler (DD) domain is proposed in this paper with dual fractional features effectively captured. Furthermore, to address the orthogonality issue of transmitted signals in the MIMO-OTFS model, a matched filter is designed based on the proposed matrix model to achieve signal separation in DD domain and extract the channel information vector associated with the target state. By exploiting the obtained channel information vector, target angle estimation is readily accomplished. For range and velocity estimation, two scenarios are considered. In separable multi-target cases, we propose the Rapid Second-Order Inversion (RSOI) algorithm to efficiently decouple and estimate individual target parameters. The Joint Particle Swarm Optimization-based Super-Resolution Algorithm (JPSO-SRA) is proposed for off-grid estimation of target parameters in inseparable multi-target cases. Extensive simulation results demonstrate that the proposed algorithms achieve more accurate target parameter sensing with lower computational complexity compared to existing methods, thereby enabling channel reconstruction in MIMO-OTFS-based ISAC systems.
{"title":"Integrated Sensing and Communication With MIMO-OTFS: Energy-Conscious Channel Reconstruction via Efficient Target Parameter Estimation","authors":"Tongmin Xiong;Yi Liao;Songjun Han;Ying-Chang Liang","doi":"10.1109/TGCN.2025.3641228","DOIUrl":"https://doi.org/10.1109/TGCN.2025.3641228","url":null,"abstract":"This paper proposes a novel OTFS (orthogonal time frequency space)-based MIMO Integrated Sensing and Communication (ISAC) system that achieves real-time channel reconstruction through advanced target parameter estimation. However, existing OTFS techniques still encounter challenges in sensing performance when applied to scenarios characterized by fractional delays and fractional Doppler frequency shifts. A novel radar channel matrix model in the delay-Doppler (DD) domain is proposed in this paper with dual fractional features effectively captured. Furthermore, to address the orthogonality issue of transmitted signals in the MIMO-OTFS model, a matched filter is designed based on the proposed matrix model to achieve signal separation in DD domain and extract the channel information vector associated with the target state. By exploiting the obtained channel information vector, target angle estimation is readily accomplished. For range and velocity estimation, two scenarios are considered. In separable multi-target cases, we propose the Rapid Second-Order Inversion (RSOI) algorithm to efficiently decouple and estimate individual target parameters. The Joint Particle Swarm Optimization-based Super-Resolution Algorithm (JPSO-SRA) is proposed for off-grid estimation of target parameters in inseparable multi-target cases. Extensive simulation results demonstrate that the proposed algorithms achieve more accurate target parameter sensing with lower computational complexity compared to existing methods, thereby enabling channel reconstruction in MIMO-OTFS-based ISAC systems.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"1552-1564"},"PeriodicalIF":6.7,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830795","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}
Intelligent reflecting surface (IRS) assisted data aggregation in Internet of Things (IoT) networks is considered in this paper, where IoT devices harvest energy from a hybrid access point (HAP) and transmit sensory data to the HAP using over-the-air computation (AirComp). Taking into account a practical non-linear energy harvesting (EH) model, we formulate an energy minimization problem under certain data aggregation accuracy requirements, which involves jointly optimizing the time allocation, beamforming at the HAP and IoT devices, and downlink/uplink IRS phase-shifts. This problem is highly intractable due to the non-convexity and variable coupling, which necessitates an alternating optimization algorithm. We first derive the time allocation ratio in closed-form and then transform the subproblem for energy beamforming to a solvable convex problem. Subsequently, the aggregation beamforming vector is optimized via majorization minimization, and the IRS phase-shifts are optimized by developing a sequential rank-one constraint relaxation based algorithm. Moreover, we investigate the optimization of both dynamic and static IRS passive beamforming. Results demonstrate that the proposed algorithm achieves a lower energy consumption than baseline algorithms. Meanwhile, the dynamic IRS beamforming possesses a superiority of reducing the energy consumption while the static IRS beamforming requires a lower computational complexity.
{"title":"IRS-Assisted Data Aggregation With Over-the-Air Computation and Non-Linear Energy Harvesting","authors":"Jiaqi Jin;Shaojun Wan;Zhibin Wang;Yuanming Shi;Yong Zhou","doi":"10.1109/TGCN.2025.3640387","DOIUrl":"https://doi.org/10.1109/TGCN.2025.3640387","url":null,"abstract":"Intelligent reflecting surface (IRS) assisted data aggregation in Internet of Things (IoT) networks is considered in this paper, where IoT devices harvest energy from a hybrid access point (HAP) and transmit sensory data to the HAP using over-the-air computation (AirComp). Taking into account a practical non-linear energy harvesting (EH) model, we formulate an energy minimization problem under certain data aggregation accuracy requirements, which involves jointly optimizing the time allocation, beamforming at the HAP and IoT devices, and downlink/uplink IRS phase-shifts. This problem is highly intractable due to the non-convexity and variable coupling, which necessitates an alternating optimization algorithm. We first derive the time allocation ratio in closed-form and then transform the subproblem for energy beamforming to a solvable convex problem. Subsequently, the aggregation beamforming vector is optimized via majorization minimization, and the IRS phase-shifts are optimized by developing a sequential rank-one constraint relaxation based algorithm. Moreover, we investigate the optimization of both dynamic and static IRS passive beamforming. Results demonstrate that the proposed algorithm achieves a lower energy consumption than baseline algorithms. Meanwhile, the dynamic IRS beamforming possesses a superiority of reducing the energy consumption while the static IRS beamforming requires a lower computational complexity.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"1591-1602"},"PeriodicalIF":6.7,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830920","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}
The industrial Internet of things (IIoT) is increasingly employing blockchain-assisted drone swarms to execute critical missions. However, due to the high energy consumption, traditional blockchain mechanisms with substantial computation overhead cannot be deployed on drones with limited power resources. To address this issue, we propose a novel renewable energy-aware consensus mechanism, named proof of green (PoG). In particular, based on the hybrid energy supply framework, we design a dynamic election strategy. To jointly optimize renewable energy consumption and historical reputation of drones, we formulate a multi-objective optimization problem to determine the optimal node selection scheme for drones. Moreover, to enhance the fairness of the election process, we introduce a verifiable random function (VRF)-based perturbation factor and integrate PoG into the Byzantine fault tolerance (BFT) voting process. Simulation results demonstrate that compared to traditional mechanisms, our scheme reduces drone battery consumption and provides robust resistance against common security threats in drone swarms.
{"title":"Renewable Energy-Aware Blockchain Consensus Architecture for Hybrid-Powered Drone Swarms","authors":"Wei Long;Jingjing Wang;Xin Zhang;Jianrui Chen;Chunxiao Jiang","doi":"10.1109/TGCN.2025.3639437","DOIUrl":"https://doi.org/10.1109/TGCN.2025.3639437","url":null,"abstract":"The industrial Internet of things (IIoT) is increasingly employing blockchain-assisted drone swarms to execute critical missions. However, due to the high energy consumption, traditional blockchain mechanisms with substantial computation overhead cannot be deployed on drones with limited power resources. To address this issue, we propose a novel renewable energy-aware consensus mechanism, named proof of green (PoG). In particular, based on the hybrid energy supply framework, we design a dynamic election strategy. To jointly optimize renewable energy consumption and historical reputation of drones, we formulate a multi-objective optimization problem to determine the optimal node selection scheme for drones. Moreover, to enhance the fairness of the election process, we introduce a verifiable random function (VRF)-based perturbation factor and integrate PoG into the Byzantine fault tolerance (BFT) voting process. Simulation results demonstrate that compared to traditional mechanisms, our scheme reduces drone battery consumption and provides robust resistance against common security threats in drone swarms.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"1525-1537"},"PeriodicalIF":6.7,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145802349","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}
Pub Date : 2025-12-01DOI: 10.1109/TGCN.2025.3639186
Anastasios Valkanis;Georgia A. Beletsioti;Konstantinos F. Kantelis;Petros Nicopolitidis;Georgios I. Papadimitriou;Malamati Louta
LoRa networks are a reliable and efficient technology for the deployment of long-range IoT networks. Their operating characteristics make them an ideal choice for the low-cost installation of sensor networks in hard-to-reach wide areas. The densification of the deployed gateways is considered as a solution to the reliability and scalability issues facing LoRa networks. However, the energy needs of the gateways require their connection and supply with the power grid. This requirement increases both installation costs and the carbon footprint of LoRa networks. The prospect of battery operated gateways connected to renewable energy resources simplifies the installation and reduces their carbon footprint. In this paper we propose a hybrid protocol that improves both the energy efficiency of the gateways and the reliability of Lora networks, making their green operation feasible. The main differentiation that the proposed protocol provides in the operation of LoRa networks, compared to the existing LoRaWAN protocol, is the dynamic and intelligent activation/deactivation of the gateways. The simulation results show that the proposed protocol greatly improves key performance metrics of LoRa networks over the existing protocol, as well as significantly reduces their carbon footprint.
{"title":"A Hybrid Protocol for Reliable and Green Operation of Multigateway LoRa Networks","authors":"Anastasios Valkanis;Georgia A. Beletsioti;Konstantinos F. Kantelis;Petros Nicopolitidis;Georgios I. Papadimitriou;Malamati Louta","doi":"10.1109/TGCN.2025.3639186","DOIUrl":"https://doi.org/10.1109/TGCN.2025.3639186","url":null,"abstract":"LoRa networks are a reliable and efficient technology for the deployment of long-range IoT networks. Their operating characteristics make them an ideal choice for the low-cost installation of sensor networks in hard-to-reach wide areas. The densification of the deployed gateways is considered as a solution to the reliability and scalability issues facing LoRa networks. However, the energy needs of the gateways require their connection and supply with the power grid. This requirement increases both installation costs and the carbon footprint of LoRa networks. The prospect of battery operated gateways connected to renewable energy resources simplifies the installation and reduces their carbon footprint. In this paper we propose a hybrid protocol that improves both the energy efficiency of the gateways and the reliability of Lora networks, making their green operation feasible. The main differentiation that the proposed protocol provides in the operation of LoRa networks, compared to the existing LoRaWAN protocol, is the dynamic and intelligent activation/deactivation of the gateways. The simulation results show that the proposed protocol greatly improves key performance metrics of LoRa networks over the existing protocol, as well as significantly reduces their carbon footprint.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"10 ","pages":"1512-1524"},"PeriodicalIF":6.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145802357","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}
Pub Date : 2025-12-01DOI: 10.1109/TGCN.2025.3634008
{"title":"IEEE Communications Society Information","authors":"","doi":"10.1109/TGCN.2025.3634008","DOIUrl":"https://doi.org/10.1109/TGCN.2025.3634008","url":null,"abstract":"","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 4","pages":"C3-C3"},"PeriodicalIF":6.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11271726","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145646088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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