IEEE Transactions on Green Communications and Networking最新文献_第4页

Secure Batch-Based Resource Allocation for Green Cognitive MIMO Indoor Flying Networks 基于批量的绿色认知多输入多输出室内飞行网络资源安全分配

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-04-11 DOI: 10.1109/TGCN.2024.3387899

Haythem Bany Salameh;Haitham Al-Obiedollah;Moayad Aloqaily

{"title":"Secure Batch-Based Resource Allocation for Green Cognitive MIMO Indoor Flying Networks","authors":"Haythem Bany Salameh;Haitham Al-Obiedollah;Moayad Aloqaily","doi":"10.1109/TGCN.2024.3387899","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3387899","url":null,"abstract":"The growing demand for advanced indoor communication capabilities in sixth-generation (6G) networks has led to extensive research into integrating Cognitive Radio (CR) and multiple-input multiple-output (MIMO) technologies with Unmanned Aerial Vehicles (UAVs). The integration of CR and MIMO with UAVs contributes to the green Open Radio Access Network (O-RAN) paradigm by leveraging CR’s advantages in interoperability, adaptability, and software-defined nature, along with UAVs’ flexible 3D movement and MIMO’s energy-efficient attributes. However, securing communication in CR-enabled MIMO-equipped UAVs in O-RAN networks against jamming attacks presents significant challenges, particularly in designing resource allocation algorithms that are both secure and energy-efficient in the presence of jamming attacks. This paper presents a secure and jamming-resistant green channel-assignment algorithm designed for indoor uplink communication in MIMO- and CR-enabled O-RAN-supported UAV networks. The proposed algorithm aims to maximize served transmissions with minimal total transmission power, exploiting MIMO, CR adaptability, and jamming awareness. Leveraging the Lagrangian technique, a closed-form formula for per-antenna power allocation is derived to solve the power minimization problem for each UAV over the available channels. Using the obtained per-UAV powers on idle channels, a power-efficient batch-based channel-assignment problem is formulated, presented as unimodular binary-linear programming solvable through polynomial-time linear programming. Compared to CR MIMO-based algorithms, the proposed algorithm significantly improves overall network performance under jamming attacks by employing user-batching with jamming awareness.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"8 3","pages":"1090-1098"},"PeriodicalIF":5.3,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142090867","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}

引用次数: 0

Learned Sharding Toward Sustainable Communications and Networking in Blockchains 学习分片，实现区块链的可持续通信和联网

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-04-10 DOI: 10.1109/TGCN.2024.3386172

Bo Yin;Rongyao Rong;Xiaoli Xiao

{"title":"Learned Sharding Toward Sustainable Communications and Networking in Blockchains","authors":"Bo Yin;Rongyao Rong;Xiaoli Xiao","doi":"10.1109/TGCN.2024.3386172","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3386172","url":null,"abstract":"Sharding scales blockchain by grouping blockchain nodes into committees each of which processes a portion of the total transactions in parallel. The issue with sharding is the enormous volume of cross-shard transactions, which results in high communication costs to ensure transaction atomicity. The account-based sharding problem can be viewed as the vertex classification problem of the account-transaction graph. However, prior studies employed traditional graph partitioning algorithms for sharding, failing to make full use of the account relationship in the graph structure. In this work, we aim to address the sharding problem from the perspective of deep learning that can learn the graph structure toward sustainable communications. We propose an efficient deep learning-based sharding scheme (DLS) based on the graph attention (GAT) network. The account and transaction information are input into the GAT for semi-supervised training and account/vertex classification. Since the performance may degrade in the case of limited label information, we incorporate the label propagation method to acquire the label information of non-trained accounts. We also extend our approach to deal with the new account scenario without retraining the neural network. Extensive experiments on Ethereum data demonstrate that our proposed DLS can effectively reduce the number of cross-shard transactions.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"8 4","pages":"1427-1439"},"PeriodicalIF":5.3,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142672198","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}

引用次数: 0

LoRaWAN Network Planning LoRaWAN 网络规划

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-04-08 DOI: 10.1109/TGCN.2024.3385707

Biswajit Paul;Chadi Assi;Georges Kaddoum

{"title":"LoRaWAN Network Planning","authors":"Biswajit Paul;Chadi Assi;Georges Kaddoum","doi":"10.1109/TGCN.2024.3385707","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3385707","url":null,"abstract":"The goal of this research is to offer recommendations on how to deploy a network more effectively by making better use of LoRaWAN features. The goals of the existing research are as follows: (i) analyzing or improving the network lifespan, delay, capacity, and interference issues, as well as (ii) the creation of network models and performance comparisons for single-hop and multi-hop routings. The authors used either analytical, simulation, or experimental framework for the evaluation of the network performance. The dilemma of how to pick/build a network model that best fits those requirements arises since each application in reality has a different set of requirements, such as lifetime, delay, coverage, connection, etc. In this research, we want to steer network designers away from selecting an available alternative that might only satisfy a portion of application needs and toward analyzing, selecting, or building a suitable network model by utilizing our proposed framework that best satisfies the application requirements. We also provide simulation data to show how the options can alter network performance. Although we limit our discussion to network lifetime, the framework provided in this paper can be easily extended following a similar methodology to incorporate any other performance concerns.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"8 4","pages":"1413-1426"},"PeriodicalIF":5.3,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142672051","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}

引用次数: 0

Energy-Efficient Carrier Aggregation in 5G Using Constrained Multi-Agent MDP 利用受限多代理 MDP 在 5G 中实现高能效载波聚合

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-04-08 DOI: 10.1109/TGCN.2024.3386066

Medhat Elsayed;Roghayeh Joda;Fahime Khoramnejad;David Chan;Akram Bin Sediq;Gary Boudreau;Melike Erol-Kantarci

{"title":"Energy-Efficient Carrier Aggregation in 5G Using Constrained Multi-Agent MDP","authors":"Medhat Elsayed;Roghayeh Joda;Fahime Khoramnejad;David Chan;Akram Bin Sediq;Gary Boudreau;Melike Erol-Kantarci","doi":"10.1109/TGCN.2024.3386066","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3386066","url":null,"abstract":"Carrier Aggregation (CA) is a promising technology in LTE and 5G networks that enhances the throughput of the users. However, since each User Equipment (UE) has to continuously monitor the activated Component Carriers (CCs) in CA, the UE energy consumption increases. To reduce the energy consumption while maximizing the throughput of UEs, we propose a dynamic and proactive CC management scheme for 5G, using a Q-Learning algorithm. To address our problem, we first model the corresponding Constrained Multi-agent Markov Decision Process (CMMDP) model and then utilize the Q-Learning algorithm to solve it. The time inter-arrival and the size of the next incoming bursts of data are proactively predicted and, along with the data in the buffer, are considered in the state space and the reward function of the machine learning model. Our proposed scheme is compared to three baseline schemes. In the first and second baseline algorithms, all CCs and only single CC are activated for each UE, respectively. For the last baseline algorithm, we simplify our Reinforcement Learning (RL) algorithm, in which the remaining data in the scheduling buffer of users is not considered and also the throughput and the number of activated CCs is balanced in the low traffic load. Simulation results reveal that our proposed Q-Learning algorithm outperforms the baselines. It achieves the same throughput as the all CC activation algorithm while reducing the UE power consumption by about 20%. These benefits are achieved by dynamically activating and deactivating CCs according to the UE traffic pattern.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"8 4","pages":"1595-1606"},"PeriodicalIF":5.3,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142713808","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}

引用次数: 0

JPC-GCE Algorithm for Energy-Efficient Wideband mmWave Systems 用于高能效宽带毫米波系统的 JPC-GCE 算法

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-04-04 DOI: 10.1109/TGCN.2024.3384554

Fulai Liu;Xinyue Lou;Dan Li;Baozhu Shi;Huifang Wang;Ruiyan Du

引用次数: 0

GCIRM: Toward Green Communication With Intelligent Resource Management Scheme for Radio Access Networks GCIRM：利用无线接入网络的智能资源管理方案实现绿色通信

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-04-03 DOI: 10.1109/TGCN.2024.3384542

Ashu Taneja;Shalli Rani;Rajesh Kumar Dhanaraj;Lewis Nkenyereye

{"title":"GCIRM: Toward Green Communication With Intelligent Resource Management Scheme for Radio Access Networks","authors":"Ashu Taneja;Shalli Rani;Rajesh Kumar Dhanaraj;Lewis Nkenyereye","doi":"10.1109/TGCN.2024.3384542","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3384542","url":null,"abstract":"With the proliferation of mobile devices and connected terminals, the mobile data traffic has witnessed an unprecedented upsurge. The increasing energy consumption owing to the massive machine type communication is the main challenge in radio access networks (RANs). Thus, energy optimized mobile networks are very important for sustainable future green communication. This paper presents an efficient approach for improving the efficiency of RAN by proposing an active-IRS aided framework. The multiple active IRSs assist the user communication by amplifying the incident signals before transmission. The system power usage is determined through a proposed power consumption model with minimum energy overhead. Further, resource management is enabled in the network through a proposed algorithm. The system rate and energy performance is obtained for different values of IRS power budget, output power and amplitude gain subject to the constraint of maximum amplification power. It is observed that maximum amplification power \u0000<inline-formula> <tex-math>$P_{max}$ </tex-math></inline-formula>\u0000 of 20 dBm yields maximum achievable rate of 16.2 bits/s/Hz. Also, the gain in energy efficiency is 20.79% when \u0000<inline-formula> <tex-math>$P_{max}$ </tex-math></inline-formula>\u0000 is changed from 0 dBm to 10 dBm. In the end, the comparison of active IRS system and passive IRS system with resource control is also carried out.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"8 3","pages":"1018-1025"},"PeriodicalIF":5.3,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142090991","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}

引用次数: 0

Jointly Power Control and Scheduling in Underwater Wireless Sensor Networks With Oblivious Freshness Requirement 具有未知新鲜度要求的水下无线传感器网络中的联合功率控制与调度

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-04-02 DOI: 10.1109/TGCN.2024.3384294

Yuchao Chen;Jintao Wang;Jun Du;Jian Song

{"title":"Jointly Power Control and Scheduling in Underwater Wireless Sensor Networks With Oblivious Freshness Requirement","authors":"Yuchao Chen;Jintao Wang;Jun Du;Jian Song","doi":"10.1109/TGCN.2024.3384294","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3384294","url":null,"abstract":"This paper considers an underwater wireless sensor network where a sink station collects time-sensitive information from multiple sensors. For timely monitoring, the sink station aims to maximize the data freshness of the entire network. The difficulty includes time-varying channel states, limited transmission bandwidth and power consumption caused by underwater acoustic communication. Moreover, due to the time-varying service requirements, the importance of data is unknown until it is received and processed by the sink station. To overcome these difficulties, we characterize the data freshness at the terminal through a set of non-decreasing functions with respect to the popular metric Age of Information (AoI). To save the energy consumption, each sensor will transmit with different power to combat the different channel states. Then, we relax the bandwidth constraint and resort to the online learning framework with Lyapunov drift analysis to design a jointly scheduling and power control algorithm based on historical observations. The algorithm is proven to achieve the sub-linear expected performance for both cumulative age regret and bandwidth violation. Finally, we propose the truncated scheduling strategy to satisfy the hard bandwidth constraint. Simulation results validate the performance of the proposed algorithms compared with the optimal offline algorithm with complete information.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"8 4","pages":"1398-1412"},"PeriodicalIF":5.3,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142672102","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}

引用次数: 0

CPNN Algorithm for Adaptive Beamforming 用于自适应波束成形的 CPNN 算法

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-03-31 DOI: 10.1109/TGCN.2024.3407980

Fulai Liu;Xuefei Sun;Zhibo Su;Ruiyan Du;Yufeng Du;Xiuquan Dou;Aiyi Zhang;Guozhu Sun

{"title":"CPNN Algorithm for Adaptive Beamforming","authors":"Fulai Liu;Xuefei Sun;Zhibo Su;Ruiyan Du;Yufeng Du;Xiuquan Dou;Aiyi Zhang;Guozhu Sun","doi":"10.1109/TGCN.2024.3407980","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3407980","url":null,"abstract":"This paper presents an effective adaptive beamforming method based on a complex-valued processing neural network (CPNN), named as CPNN algorithm. In the proposed method, the optimal beamforming problem can be formulated as a regression problem of neural networks (NNs). In the CPNN structure, a new real-imaginary merging (RIM) layer and a new imaginary-real merging (IRM) layer are constructed to process complex-valued data with other layers. Via the RIM and IRM layers, the complex-valued data computation in the neurons follows the complex-valued multiplication rule, which makes the mathematical relationship between the input and output of the NN-based beamformer more reasonable. Compared with the previous works in NNs, the proposed CPNN approach provides better beamforming performance, for example, 1) the phase information of the complex-valued data is maintained, which makes the output of the NN-based beamformer more accurate; 2) it does not require prior information of the desired signal, such as the desired direction of arrival, which will avoid errors caused by signal parameters estimation; and 3) it can not only effectively suppress the interference signals but also ensure that the response of the desired signal is distortionless. Simulation results demonstrate the efficiency of the presented approach.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"8 4","pages":"1521-1529"},"PeriodicalIF":5.3,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142672034","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}

引用次数: 0

Coordinated Link Adaptation for an Energy-Efficient Full-Duplex Random Access Network 高能效全双工随机存取网络的协调链路自适应

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-03-31 DOI: 10.1109/TGCN.2024.3407764

Huu-Hung Tran;Ji-Hoon Yun

{"title":"Coordinated Link Adaptation for an Energy-Efficient Full-Duplex Random Access Network","authors":"Huu-Hung Tran;Ji-Hoon Yun","doi":"10.1109/TGCN.2024.3407764","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3407764","url":null,"abstract":"In this paper, we develop a coordinated link adaptation scheme to maximize the energy efficiency of a full-duplex (FD) random access network when self-interference cancellation (SIC) is imperfect. First, we model the energy consumption of an FD link and formulate an energy-consumption-per-bit minimization problem with the constellation size of the link as a problem variable. Via numerical results, the model shows that the optimal constellation size of an FD link strongly depends on not only the communication distance but also the SIC capability and data length. Then, we extend the formulation to the energy-consumption minimization problem for an FD random access network. A conservative delay budget for saturated traffic conditions is obtained in terms of the constellation sizes of the associated devices. Finally, the network coordination problem for the constellation sizes is formulated as a nonlinear problem with integer constraints on the constellation sizes, and a solution algorithm for this problem is designed, employing the successive convex approximation method. A comparative evaluation with representative conventional schemes demonstrates that the proposed scheme significantly outperforms the conventional schemes in terms of the energy consumption per bit for a wide range of network environments.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"8 4","pages":"1692-1706"},"PeriodicalIF":5.3,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142713766","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}

引用次数: 0

Cooperative Throughput Maximization in a Multi-Cluster WPCN 多集群 WPCN 中的合作吞吐量最大化

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-03-30 DOI: 10.1109/TGCN.2024.3407522

Omid Rezaei;Maryam Masjedi;Mohammad Mahdi Naghsh;Saeed Gazor;Mohammad Mahdi Nayebi

{"title":"Cooperative Throughput Maximization in a Multi-Cluster WPCN","authors":"Omid Rezaei;Maryam Masjedi;Mohammad Mahdi Naghsh;Saeed Gazor;Mohammad Mahdi Nayebi","doi":"10.1109/TGCN.2024.3407522","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3407522","url":null,"abstract":"This paper investigates a multi-cluster Wireless Powered Communication Network (WPCN) where user clusters cooperate with a Cluster Head (CH) and a Hybrid Access Point (HAP). Employing beamforming, the HAP supplies energy in the downlink phase, while users transmit signals to the HAP and CHs in the uplink phase. We optimize the Energy Beamforming (EB) matrix, user transmit covariance matrices, and time slot allocation to enhance both max-min and sum network throughput. To tackle the non-convexity of the optimization problems, we decompose them into two subproblems and reformulate each as convex Second Order Cone Programming (SOCP) and Quadratic Constraint Quadratic Programming (QCQP) for the max-min and sum throughput problems, respectively. Notably, we account for imperfections in Channel State Information (CSI) and non-linear Energy Harvesting (EH) circuits. Additionally, we incorporate the active Intelligent Reflecting Surfaces (IRS) as a key component in our proposed method. Numerical examples illustrate the significant impact of these contributions across various scenarios.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"8 4","pages":"1505-1520"},"PeriodicalIF":5.3,"publicationDate":"2024-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142671998","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}

引用次数: 0