Heng Chang;Xueyu Kang;Hongjiang Lei;Theodoros A. Tsiftsis;Gaofeng Pan;Hongwu Liu
{"title":"STAR-RIS-Aided Covert Communications in MISO-RSMA Systems","authors":"Heng Chang;Xueyu Kang;Hongjiang Lei;Theodoros A. Tsiftsis;Gaofeng Pan;Hongwu Liu","doi":"10.1109/TGCN.2024.3432656","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3432656","url":null,"abstract":"In this paper, a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) is deployed to aid covert communications in a multiple-input single-output (MISO) rate-splitting multiple access (RSMA) system. To maximize the covert communication rate, which is characterized by the shared common rate and private rate of the covert user, the transmit beamforming, reflection/refraction beamforming, and common rate allocation need to be jointly optimized. By decoupling the original covert communication rate maximization problem into three sub-problems, an alternating optimization (AO) algorithm is designed to obtain the optimized solution to achieve the maximum covert communication rate. For the sub-problem of optimizing the common rate allocation, a closed-form expression is derived for the optimal common rate allocation. For the multiple-ratio fractional programming sub-problems of optimizing the transmit beamforming and reflection/refraction beamforming, Lagrangian dual formulation and quadratic transformation are utilized to reconstruct the objective function in the form difference of convex functions. Then, a penalized successive convex approximation is utilized to tackle the rank-one constrained beamforming optimization. Simulation results clarify the effectiveness of the proposed AO algorithm to achieve the maximum covert communication rate. Compared to the benchmark scheme in which the common rate allocation is missing, it is verified by simulation results that the STAR-RIS-aided MISO-RSMA scheme effectively increases the covert communication rate.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"8 4","pages":"1318-1331"},"PeriodicalIF":5.3,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142672039","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":"Task Dependency Aware Optimal Resource Allocation for URLLC Edge Network: A Digital Twin Approach Using Finite Blocklength","authors":"Muhammad Awais;Haris Pervaiz;Qiang Ni;Wenjuan Yu","doi":"10.1109/TGCN.2024.3425442","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3425442","url":null,"abstract":"Next-generation wireless networks envision ubiquitous access and computational capabilities by seamlessly integrating aerial and terrestrial networks. Digital twin (DT) technology emerges as a proactive and cost-effective approach for resource-limited networks. Mobile edge computing (MEC) is pivotal in facilitating mobile offloading, particularly under the demanding constraints of ultra-reliable and low-latency communication (URLLC). This study proposes an advanced bisection sampling-based stochastic solution enhancement (BSSE) algorithm to minimize the system’s overall energy-time cost by jointly optimizing task offloading and resource allocation strategies. The formulated problem is a mixed-integer nonlinear programming problem due to its inherently combinatorial linkage with task-offloading decisions and strong correlation with resource allocation. The proposed algorithm operates iteratively through the following steps: 1) narrowing the search space through a one-climb policy, 2) developing a closed-form solution for optimal CPU frequency and transmit power, and 3) implementing randomized task offloading, which updates it in the direction of reducing objective value. The scalability of the proposed algorithm is also analyzed for a two-device model, which is subsequently extended to multiple devices. Comparative analysis against benchmark schemes reveals that our approach reduces total energy-time cost by 15.35% to 33.12% when weighting parameter <inline-formula> <tex-math>$partial ^{lambda }_{k_{2}}$ </tex-math></inline-formula> is increased from 0.1 to 0.3, respectively.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 1","pages":"177-190"},"PeriodicalIF":5.3,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430350","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":"Beamforming Design for Cooperative Double-RIS Aided mmWave MU-MIMO Communications","authors":"Qing Xue;Renlong Wei;Zhidu Li;Yanping Liu;Yongjun Xu;Qianbin Chen","doi":"10.1109/TGCN.2024.3427126","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3427126","url":null,"abstract":"This research delves into the design of collaborative beamforming for millimeter-wave (mmWave) multi-user multiple-input multiple-output (MU-MIMO) communications, which takes advantage of double reconfigurable intelligent surfaces (RISs) for enhanced signal transmission. The core objective is to jointly optimize the transmit beamforming at the base station and the phase shifts of the RISs to achieve the highest possible sum rate. To derive an efficient solution, the original problem is recast using the weighted minimum mean square error (WMMSE) approach, paving the way for an equivalent problem formulation. An effective alternating optimization strategy is introduced to tackle this problem, sequentially adjusting the transmit beamforming matrix and the RIS phase shifts for near-optimal results. In particular, a specialized WMMSE-based algorithm is devised for designing the transmit beamforming, while the passive beamforming of the RIS is optimized through semi-definite relaxation and majorization-minimization techniques. This balance ensures both high system performance and manageable computational load. Further analysis delves into the convergence properties and computational demands of the proposed methods. Simulation results are presented to validate the efficacy of the proposed algorithm and demonstrate the enhanced spectral efficiency achieved through the utilization of the double-RIS.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 2","pages":"645-657"},"PeriodicalIF":5.3,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117226","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":"Multi-Round Stackelberg Game-Based Pricing and Offloading in Containerized MEC Networks","authors":"Mingxiong Zhao;Zhaojie Yang;Zhenli He;Fanhao Xue;Xianqi Zhang","doi":"10.1109/TGCN.2024.3425643","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3425643","url":null,"abstract":"Mobile Edge Computing (MEC) tackles the challenges associated with the rapid proliferation of User Equipment (UE) and limited computing resources. Containerization, essential for MEC deployments, encapsulates applications and dependencies, optimizing resource utilization. In containerized MEC networks, UEs offload computational tasks to edge server containers, enabling service providers to profit from offering scalable and portable services, thereby establishing a symbiotic economic ecosystem. However, traditional models, which often separate cost and delay assessments, fail to consider these factors holistically. Furthermore, they underutilize the potential of container images’ hierarchical structure, which could optimize storage and reduce costs. Our research introduces a novel multi-round Stackelberg game framework that incorporates the hierarchical structure of container images to enhance resource management in MEC networks. Additionally, we integrate discount rates to model long-term economic interactions accurately, and develop two innovative algorithms: the Distributed Ant Colony Pricing (DACP) and the Multi-Round Simulated Annealing Pricing (MRSAP). These algorithms account for both immediate and long-term impacts, redefining user utility and significantly improving system efficiency. Simulation results validate the effectiveness of our algorithms in optimizing resource allocation and enhancing efficiency in dynamic MEC scenarios.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 1","pages":"191-206"},"PeriodicalIF":5.3,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430355","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":"Statistical Analysis and Energy-Efficient Routing for Tsunami Early Alarming in Internet of Underwater Things Using SDN Infrastructure","authors":"Shahrzad Sedaghat;Amir Hossein Jahangir","doi":"10.1109/TGCN.2024.3426307","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3426307","url":null,"abstract":"This paper presents a novel, energy-efficient routing approach for underwater sensor networks in tsunami early warning. Our system utilizes sensor nodes equipped with piezoelectric energy harvesting to extend network lifetime and stability. Continuous sensing is replaced with a duty-cycled approach to conserve energy, where the ocean surface is divided into regions and sensor nodes are grouped. These groups become active at designated intervals, while others remain dormant. The system leverages satellite networks to complement the underwater sensor network, enabling collected data to reach the central hub of early warning systems. A statistical analysis assigns scores to potential routes based on their energy consumption, prioritizing low-energy paths. Probability theory is employed to calculate the minimum number of transmission paths needed to achieve a predetermined level of reliability. A well-established tsunami wave prediction system is used to select the most suitable next hop for data transmission to avoid interference with tsunami wave propagation. Simulation results demonstrate significant improvements in energy efficiency, end-to-end delay, sensor and relay node lifespan, and network stability compared to recent research. These achievements highlight the effectiveness of our proposed routing approach in achieving energy efficiency and reliable data transmission within a tsunami early warning system.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 2","pages":"561-573"},"PeriodicalIF":5.3,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117178","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":"Efficient Charging and Data Collection in UAV-Aided Backscatter Sensor Networks","authors":"Amit Goel;Nancy Varshney;Swades De","doi":"10.1109/TGCN.2024.3426356","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3426356","url":null,"abstract":"Backscatter communication based wireless charging of the sensor nodes and data collection from them is a promising solution due to ultra-low power consumption. However, challenges of short transmission range requirement, high self-interference, and simultaneous operation with multiple backscatter nodes (BSNs) need to be addressed. To this end, this paper presents a novel framework for joint field data collection and wireless charging in an unmanned aerial vehicle (UAV)-aided wireless sensor network via monostatic backscatter communication at millimeter waves. The framework is divided into three tasks, namely, energy-optimized UAV transceiver design, UAV constraints aware BSN clustering, and optimized resource allocation per cluster. To strike a balance between serving efficiency and self-interference, optimum BSN cluster size is estimated offline, which in turn governs BSN clustering optimization. With UAV communication energy and clustering information, a joint sum energy transfer and sum data collection maximization problem is formulated by considering the minimum required charging and data collection constraints. To handle non-convexity, an alternating optimization approach is devised, estimating optimal backscatter reflection coefficients, data collection time, and power distribution among the BSNs using successive convex approximation. Finally, via Monte-Carlo simulations, performance of the proposed system is compared with the current state-of-the-art.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 2","pages":"574-587"},"PeriodicalIF":5.3,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117439","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":"Toward Sustainable O-RAN Deployment: An In-Depth Analysis of Power Consumption","authors":"Gianmarco Baldini;Raffaele Bolla;Roberto Bruschi;Alessandro Carrega;Franco Davoli;Chiara Lombardo;Ramin Rabbani","doi":"10.1109/TGCN.2024.3426108","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3426108","url":null,"abstract":"5G delivers limitless mobile broadband capabilities, enabling extensive connectivity for various devices, including smartphones, sensors, and machines. Its most notable feature lies in its ability to facilitate instantaneous and highly reliable machine communications. Because of the rapid evolution of communication networks, innovative architectures such as Open RAN (O-RAN) have emerged, promising increased flexibility, efficiency, and sustainability. To realize the full potential of ORAN networks, however, it is critical to understand their power consumption implications. In this paper, in order to understand the way O-RAN consumes energy, a comprehensive power consumption model is used. The study not only provides theoretical analysis but also incorporates a practical implementation of the architecture. For this, an algorithm is employed to determine a base monolithic architecture of O-RAN by the placement of Distributed Unit (DU) and Centralized Unit (CU) using available data of Radio Unit (RU) in France and Ireland. The research further explores the impact of different parameter variations in various Evaluation Scenarios (ESs) on the architecture. By conducting this thorough evaluation, this research provides valuable insights for researchers and industry practitioners to gain a deeper understanding of energy consumption patterns and derive ideas on how to effectively reduce power consumption in these networks.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 2","pages":"429-444"},"PeriodicalIF":5.3,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10592054","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117444","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}
{"title":"Federated Learning-Enabled Jamming Detection for Stochastic Terrestrial and Non-Terrestrial Networks","authors":"Aida Meftah;Tri Nhu Do;Georges Kaddoum;Chamseddine Talhi","doi":"10.1109/TGCN.2024.3425792","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3425792","url":null,"abstract":"In this paper, we present a novel federated learning (FL) algorithm, named Aggregated and Augmented Training Federated (AAT-Fed), tailored for stochastic, distributed, tactical terrestrial and non-terrestrial (SDT-TNT) network environments. Focusing on an SDT-TNT network with multiple clusters and potential unknown jammers, our approach addresses jammer detection through convolutional variational autoencoders (C-VAEs) within the FL framework. Leveraging the spectral correlation function (SCF) of the in-phase and quadrature (I/Q) representation of received signals, our method extracts discriminating features for jammer detection in the absence of prior knowledge about the jammers. AAT-Fed excels at managing the unique characteristics of the tactical TNT network, considering its stochastic nature and the heterogeneity in data distribution between network cells, leading to enhanced jamming detection accuracy. Comparative simulation results demonstrate AAT-Fed’s superior performance over FL and non-FL approaches, showcasing its effectiveness in providing accurate jamming detection at a low jamming-to-noise ratio.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 1","pages":"271-290"},"PeriodicalIF":5.3,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430401","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 Optimization of Semi-Passive IRS Phase Shifts and NOMA Power Coefficients for Cooperative CRNs","authors":"Mohsin Khan;Jawad Mirza;Bakhtiar Ali;Muhammad Awais Javed;Kapal Dev;Lewis Nkenyereye;Paolo Bellavista","doi":"10.1109/TGCN.2024.3426305","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3426305","url":null,"abstract":"We investigate the incorporation of an intelligent reflecting surface (IRS) into cooperative spectrum-sharing cognitive radio networks (CRNs). The CRN consists of a primary user (PU) and multiple secondary users (SUs). There are two transmission phases. In the first phase, the primary transmitter is assisted by an IRS to serve the primary user (PU). This arrangement allows the primary network to allocate a part of its spectrum to the users within the secondary network. In the subsequent phase, the secondary transmitter (ST) employs a non-orthogonal multiple access (NOMA) transmission technique to simultaneously serve the PU and secondary users (SUs). By utilizing a semi-passive IRS, both data transmission to the PU and channel estimation of SUs are performed simultaneously during the first transmission phase. The main objective is to improve the weighted sum-rate of the CRN through a joint optimization of the NOMA power coefficients and IRS phase adjustments during the second transmission phase. We propose an effective algorithm that breaks down the primary sum-rate maximization problem into two sub-problems where IRS phase shifts are computed once at the beginning of the algorithm. Through simulations, we demonstrate that the proposed algorithm yields substantial gains in the sum-rate performance compared to existing methods.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 1","pages":"380-391"},"PeriodicalIF":5.3,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403784","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-Spectral Efficiency Trade-Off in IRS-Assisted NOMA Systems: A Weighted Product Method","authors":"Haitham Al-Obiedollah;Haythem Bany Salameh;Sharief Abdel-Razeq","doi":"10.1109/TGCN.2024.3426311","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3426311","url":null,"abstract":"The deployment of intelligent reflecting surfaces (IRS) in non-orthogonal multiple access (NOMA), known as IRS-assisted NOMA-based systems, has recently been considered a potential solution to address the complicated demands of beyond-fifth-generation communication networks. This paper investigates a multi-objective allocation resource allocation technique for an IR-assisted hybrid time division multiple access (TDMA)-NOMA network. To reflect the requirements of such a system, two conflicting performance metrics, namely energy efficiency (EE) and spectral efficiency (SE), are simultaneously optimized under a set of quality-of-service constraints. The proposed SE-EE trade-off design is formulated as a multi-objective optimization (MOO) framework. However, such an MOO problem cannot be solved by conventional approaches. Therefore, the weighted product method (WPM) is proposed to transform the MOO problem into a conventional single-objective optimization (SOO) problem. Meanwhile, the SOO problem through the WPM approach is non-convex in nature, where the optimization parameters, namely the power allocation and the reflecting coefficients of the IRS elements, are jointly designed. As a result, an iterative technique is designed to address this problem and assess the optimization variables. The simulation results demonstrate that the proposed WPM for the SE-EE trade-off resource allocation technique can balance competing optimization variables alongside meeting the system’s demands.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 2","pages":"635-644"},"PeriodicalIF":5.3,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117443","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}