Pub Date : 2024-11-26DOI: 10.1109/TGCN.2024.3506153
{"title":"2024 Index IEEE Transactions on Green Communications and Networking Vol. 8","authors":"","doi":"10.1109/TGCN.2024.3506153","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3506153","url":null,"abstract":"","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"8 4","pages":"1-35"},"PeriodicalIF":5.3,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10768869","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142713816","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 : 2024-11-21DOI: 10.1109/TGCN.2024.3503687
Zhichao Sheng;Hao Hu;Ali A. Nasir;Yong Fang;Daniel B. da Costa
We consider a mobile edge computing (MEC) framework empowered by unmanned aerial vehicle (UAV) and reflecting intelligent surface (RIS) serving multiple ground users in a practical environment, where mobile ground users generate movements and tasks randomly. Our objective is to optimize energy efficiency while ensuring long-term data queue stability, assuming knowledge of the channel state information. The problem is formulated as a stochastic optimization problem, and the Lyapunov method is applied to convert the initial problem into per-slot problems. Without the future knowledge of user movement, we consider the outage constraint into the per-slot problem to derive robust resource allocation and trajectory design in the MEC system. For each per-slot problem, an alternating optimization algorithm utilizing successive convex approximation technique is designed to solve it. This solution guarantees adherence to the UAV energy budget constraint while achieving a balance between system energy efficiency and the length of the queue backlog. Simulation results demonstrate that the proposed algorithm achieves better performance than other benchmark methods in terms of improving energy efficiency and maintaining queue stability.
{"title":"Online Trajectory Planning and Resource Allocation of UAV-Enabled MEC Networks Empowered by RIS","authors":"Zhichao Sheng;Hao Hu;Ali A. Nasir;Yong Fang;Daniel B. da Costa","doi":"10.1109/TGCN.2024.3503687","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3503687","url":null,"abstract":"We consider a mobile edge computing (MEC) framework empowered by unmanned aerial vehicle (UAV) and reflecting intelligent surface (RIS) serving multiple ground users in a practical environment, where mobile ground users generate movements and tasks randomly. Our objective is to optimize energy efficiency while ensuring long-term data queue stability, assuming knowledge of the channel state information. The problem is formulated as a stochastic optimization problem, and the Lyapunov method is applied to convert the initial problem into per-slot problems. Without the future knowledge of user movement, we consider the outage constraint into the per-slot problem to derive robust resource allocation and trajectory design in the MEC system. For each per-slot problem, an alternating optimization algorithm utilizing successive convex approximation technique is designed to solve it. This solution guarantees adherence to the UAV energy budget constraint while achieving a balance between system energy efficiency and the length of the queue backlog. Simulation results demonstrate that the proposed algorithm achieves better performance than other benchmark methods in terms of improving energy efficiency and maintaining queue stability.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 3","pages":"1224-1238"},"PeriodicalIF":6.7,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144880612","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 : 2024-11-21DOI: 10.1109/TGCN.2024.3502072
Rojin Aslani;Ebrahim Saberinia
Unmanned aerial vehicles (UAVs) have emerged as pivotal mobile base stations (UAV-BSs) for vehicular communications, particularly in regions without terrestrial infrastructure. This paper deploys multiple UAV-BSs to cover a highway segment devoid of existing infrastructure. We introduce and compare two UAV-BS deployment strategies: hovering and flying, taking into account their distinct specifications. We assume full-duplex (FD) UAV-BSs facilitate both uplink (UL) and downlink (DL) communication for half-duplex (HD) vehicular users. These systems grapple with self-interference from FD UAV-BSs, interference among HD vehicular users, and inter-carrier interference (ICI) resulting from the Doppler effect induced by mobility, ultimately affecting the quality of service (QoS) for vehicular users. To address this challenge, we propose a resource allocation scheme for both systems, optimizing power allocation and frequency assignment to maximize system data rate while ensuring QoS in both UL and DL. Through theoretical analysis, we compare the computational complexity of the resource allocation scheme between the two systems. Our simulation results show the advantages of the flying UAV-BSs system, particularly in terms of a higher system data rate, an increased probability of feasibility, a reduced number of required UAV-BSs, a lower vehicular user outage ratio, and the potential for lower computational complexity in resource allocation.
{"title":"Efficient UAV Deployment for Vehicular Communications in Highway Scenarios: Hovering or Flying?","authors":"Rojin Aslani;Ebrahim Saberinia","doi":"10.1109/TGCN.2024.3502072","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3502072","url":null,"abstract":"Unmanned aerial vehicles (UAVs) have emerged as pivotal mobile base stations (UAV-BSs) for vehicular communications, particularly in regions without terrestrial infrastructure. This paper deploys multiple UAV-BSs to cover a highway segment devoid of existing infrastructure. We introduce and compare two UAV-BS deployment strategies: hovering and flying, taking into account their distinct specifications. We assume full-duplex (FD) UAV-BSs facilitate both uplink (UL) and downlink (DL) communication for half-duplex (HD) vehicular users. These systems grapple with self-interference from FD UAV-BSs, interference among HD vehicular users, and inter-carrier interference (ICI) resulting from the Doppler effect induced by mobility, ultimately affecting the quality of service (QoS) for vehicular users. To address this challenge, we propose a resource allocation scheme for both systems, optimizing power allocation and frequency assignment to maximize system data rate while ensuring QoS in both UL and DL. Through theoretical analysis, we compare the computational complexity of the resource allocation scheme between the two systems. Our simulation results show the advantages of the flying UAV-BSs system, particularly in terms of a higher system data rate, an increased probability of feasibility, a reduced number of required UAV-BSs, a lower vehicular user outage ratio, and the potential for lower computational complexity in resource allocation.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 3","pages":"857-872"},"PeriodicalIF":6.7,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144887719","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 : 2024-11-19DOI: 10.1109/TGCN.2024.3454935
Yijie Mao;Bruno Clerckx;Derrick Wing Kwan Ng;Wolfgang Utschick;Ying Cui;Timothy N. Davidson
{"title":"Guest Editorial Special Issue on Rate-Splitting Multiple Access for Future Green Communication Networks","authors":"Yijie Mao;Bruno Clerckx;Derrick Wing Kwan Ng;Wolfgang Utschick;Ying Cui;Timothy N. Davidson","doi":"10.1109/TGCN.2024.3454935","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3454935","url":null,"abstract":"","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"8 4","pages":"1291-1292"},"PeriodicalIF":5.3,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10758386","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142672003","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 : 2024-11-19DOI: 10.1109/TGCN.2024.3494575
{"title":"IEEE Transactions on Green Communications and Networking","authors":"","doi":"10.1109/TGCN.2024.3494575","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3494575","url":null,"abstract":"","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"8 4","pages":"C2-C2"},"PeriodicalIF":5.3,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10758387","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142672040","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 : 2024-11-19DOI: 10.1109/TGCN.2024.3494577
{"title":"IEEE Communications Society Information","authors":"","doi":"10.1109/TGCN.2024.3494577","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3494577","url":null,"abstract":"","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"8 4","pages":"C3-C3"},"PeriodicalIF":5.3,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10758388","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142679361","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 : 2024-11-19DOI: 10.1109/TGCN.2024.3489606
Omid M. Kandelusy;Taejoon Kim
The distributed diversity reception with quantization and fusion has garnered considerable attention for improved reliability. In this paper, we introduce a novel buffer-aided distributed compressed transmission and fusion (DCTF) technique to cope with the fading effect and to improve the energy consumption of wireless sensor networks (WSNs). Exploiting the transmission flexibility enabled by data buffering, we design an optimal communication protocol by maximizing the average fusion rate at the FC subject to reliability, spectral efficiency, and energy consumption constraints. Unlike prior distributed reception schemes, our approach does not require any subjective quantization level setting; the compression rate in our approach is optimized by maximizing the average fusion rate. Based on the optimized compression rate, we develop two adaptive protocols, namely, adaptive multi-rate (AMR) and its simplified version, adaptive on-off (AOO). In contrast to the non-buffered scheme, the flexibility offered by buffering is exploited in our approach to lower the battery drainage in conjunction with opportunistic energy harvesting (EH). Through Monte-Carlo simulations we evaluate the performance of the proposed protocols under different scenarios and in comparison to the non-adaptive benchmark. Findings reveal that the proposed methodologies outperform conventional schemes in terms of reliability, energy consumption, and average fusion rate.
{"title":"Buffer-Aided Distributed Compressed Transmission and Fusion Under Energy and Reliability Constraints","authors":"Omid M. Kandelusy;Taejoon Kim","doi":"10.1109/TGCN.2024.3489606","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3489606","url":null,"abstract":"The distributed diversity reception with quantization and fusion has garnered considerable attention for improved reliability. In this paper, we introduce a novel buffer-aided distributed compressed transmission and fusion (DCTF) technique to cope with the fading effect and to improve the energy consumption of wireless sensor networks (WSNs). Exploiting the transmission flexibility enabled by data buffering, we design an optimal communication protocol by maximizing the average fusion rate at the FC subject to reliability, spectral efficiency, and energy consumption constraints. Unlike prior distributed reception schemes, our approach does not require any subjective quantization level setting; the compression rate in our approach is optimized by maximizing the average fusion rate. Based on the optimized compression rate, we develop two adaptive protocols, namely, adaptive multi-rate (AMR) and its simplified version, adaptive on-off (AOO). In contrast to the non-buffered scheme, the flexibility offered by buffering is exploited in our approach to lower the battery drainage in conjunction with opportunistic energy harvesting (EH). Through Monte-Carlo simulations we evaluate the performance of the proposed protocols under different scenarios and in comparison to the non-adaptive benchmark. Findings reveal that the proposed methodologies outperform conventional schemes in terms of reliability, energy consumption, and average fusion rate.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 3","pages":"789-801"},"PeriodicalIF":6.7,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144887720","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 : 2024-11-18DOI: 10.1109/TGCN.2024.3500098
Qixin Luo;Bing Xiang;Zhijia Li;Ruoxuan Zhou;Zihua Fang;Liang Lang
Magnetic induction wireless sensors are widely used in extreme environments due to their advantages. In this paper, we study robust beamforming technology to enhance the power efficiency of wireless sensor charging networks. Our approach utilizes three orthogonally deployed coils (3D-coil) as transmitters and accounts for the uncertainty of magnetic mutual inductance information (MII) caused by random angles. The beamforming optimization problem is reformulated into two cases: the perfect MII problem and the imperfect MII problem. In the scenario of perfect MII, the penalty-based successive convex approximation (SCA) method is employed to solve the rank-one constrained positive semi-definite programming problem. For the imperfect MII case, we establish the 3D-coil polarization factor model. We combine the semi-definite programming relaxation method with the penalty-based SCA method to achieve approximately optimal beamforming. Specifically, we first use the Taylor expansion approximation method, semi-definite relaxation, and the S-lemma to convert the semi-infinite constraints into finite-form constraints. Then, we propose a penalty-based SCA algorithm to obtain the Karush-Kuhn-Tucker (KKT) solution that satisfies the conditions. Simulation results verify the superiority of the proposed scheme in terms of power transmission reliability and efficiency, providing a theoretical basis for the practical application of magnetic wireless power transfer (WPT) technology.
{"title":"Magnetic Robust Energy Beamforming for Wireless Sensor Networks","authors":"Qixin Luo;Bing Xiang;Zhijia Li;Ruoxuan Zhou;Zihua Fang;Liang Lang","doi":"10.1109/TGCN.2024.3500098","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3500098","url":null,"abstract":"Magnetic induction wireless sensors are widely used in extreme environments due to their advantages. In this paper, we study robust beamforming technology to enhance the power efficiency of wireless sensor charging networks. Our approach utilizes three orthogonally deployed coils (3D-coil) as transmitters and accounts for the uncertainty of magnetic mutual inductance information (MII) caused by random angles. The beamforming optimization problem is reformulated into two cases: the perfect MII problem and the imperfect MII problem. In the scenario of perfect MII, the penalty-based successive convex approximation (SCA) method is employed to solve the rank-one constrained positive semi-definite programming problem. For the imperfect MII case, we establish the 3D-coil polarization factor model. We combine the semi-definite programming relaxation method with the penalty-based SCA method to achieve approximately optimal beamforming. Specifically, we first use the Taylor expansion approximation method, semi-definite relaxation, and the S-lemma to convert the semi-infinite constraints into finite-form constraints. Then, we propose a penalty-based SCA algorithm to obtain the Karush-Kuhn-Tucker (KKT) solution that satisfies the conditions. Simulation results verify the superiority of the proposed scheme in terms of power transmission reliability and efficiency, providing a theoretical basis for the practical application of magnetic wireless power transfer (WPT) technology.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 3","pages":"844-856"},"PeriodicalIF":6.7,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144887852","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 : 2024-11-14DOI: 10.1109/TGCN.2024.3498833
Hanjie Wu;Youyang Xiang;Xiantao Cheng
This paper investigates the ergodic capacity for uplink multi-user multiple-input multiple-output (MU-MIMO) systems, in which base station (BS) bears a mixed analog-to-digital converter (ADC) architecture, i.e., different BS antennas are connected to the ADCs with different resolution levels. We consider two quantization models: approximate linear model and precise nonlinear model. By resorting to the replica method in statistical physics, we elaborately derive the ergodic capacity for arbitrary signalling inputs. With this, one can easily obtain the analytical capacity expressions for the often-used Gaussian inputs and QAM inputs. Through Monte Carlo simulations, it is found that: (1) For Gaussian inputs, the analytical capacity expression of the nonlinear quantization model is more accurate than that of the linear model. (2) For QAM inputs, the linear model is not applicable and one should resort to the nonlinear model for capacity analysis. (3) For QAM inputs, the analytical results of the nonlinear model match well with simulations. These observations are in line with the expectation, since the nonlinear model, instead of the linear model, accurately embodies the quantization process. Furthermore, with the obtained capacity expressions, we optimize the resolution profile of the BS ADCs to reduce the energy consumption under various scenarios.
{"title":"Ergodic Capacity Analysis and Resolution Optimization for Uplink MU-MIMO Systems With Mixed ADCs","authors":"Hanjie Wu;Youyang Xiang;Xiantao Cheng","doi":"10.1109/TGCN.2024.3498833","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3498833","url":null,"abstract":"This paper investigates the ergodic capacity for uplink multi-user multiple-input multiple-output (MU-MIMO) systems, in which base station (BS) bears a mixed analog-to-digital converter (ADC) architecture, i.e., different BS antennas are connected to the ADCs with different resolution levels. We consider two quantization models: approximate linear model and precise nonlinear model. By resorting to the replica method in statistical physics, we elaborately derive the ergodic capacity for arbitrary signalling inputs. With this, one can easily obtain the analytical capacity expressions for the often-used Gaussian inputs and QAM inputs. Through Monte Carlo simulations, it is found that: <xref>(1)</xref> For Gaussian inputs, the analytical capacity expression of the nonlinear quantization model is more accurate than that of the linear model. <xref>(2)</xref> For QAM inputs, the linear model is not applicable and one should resort to the nonlinear model for capacity analysis. <xref>(3)</xref> For QAM inputs, the analytical results of the nonlinear model match well with simulations. These observations are in line with the expectation, since the nonlinear model, instead of the linear model, accurately embodies the quantization process. Furthermore, with the obtained capacity expressions, we optimize the resolution profile of the BS ADCs to reduce the energy consumption under various scenarios.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 3","pages":"829-843"},"PeriodicalIF":6.7,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144887756","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 : 2024-11-14DOI: 10.1109/TGCN.2024.3498834
Muddasir Rahim;Thanh Luan Nguyen;Georges Kaddoum
In this paper, we examine coexistence of enhanced mobile broadband (eMBB) and ultra-reliable low-latency communication (URLLC) services within an intelligent reconfigurable surface (IRS)-assisted terahertz multi-cell network. The simultaneous operation of eMBB and URLLC services in the same network poses significant resource management (RM) challenges. To address this concern, we propose a joint power, user, and service allocation (JPUSA) framework. This optimization, which is a multi-objective optimization problem, aims to maximize the eMBB data rate while ensuring URLLC reliability. It is a challenging NP-hard mixed-integer nonlinear programming problem. We propose a weighted sum method to convert it into a single-objective optimization problem, decomposing it into eMBB and URLLC RM sub-problems. Specifically, a one-to-many matching game is introduced to allocate IRSs to eMBB users, and a puncturing technique is used to assign eMBB resources to URLLC users. Simulation results reveal a superior performance of the proposed scheme over baseline methods, particularly in terms of the eMBB sum data rates and URLLC reliability. Additionally, the proposed algorithm’s sum rate for eMBB users closely approximates that of an exhaustive search (ES) method. The results of our complexity analysis demonstrate that the proposed scheme has a lower computational complexity as compared to the ES scheme.
{"title":"JPUSA in Coexistence of eMBB and URLLC Services in Multi-Cell IRS-Assisted Terahertz Networks","authors":"Muddasir Rahim;Thanh Luan Nguyen;Georges Kaddoum","doi":"10.1109/TGCN.2024.3498834","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3498834","url":null,"abstract":"In this paper, we examine coexistence of enhanced mobile broadband (eMBB) and ultra-reliable low-latency communication (URLLC) services within an intelligent reconfigurable surface (IRS)-assisted terahertz multi-cell network. The simultaneous operation of eMBB and URLLC services in the same network poses significant resource management (RM) challenges. To address this concern, we propose a joint power, user, and service allocation (JPUSA) framework. This optimization, which is a multi-objective optimization problem, aims to maximize the eMBB data rate while ensuring URLLC reliability. It is a challenging NP-hard mixed-integer nonlinear programming problem. We propose a weighted sum method to convert it into a single-objective optimization problem, decomposing it into eMBB and URLLC RM sub-problems. Specifically, a one-to-many matching game is introduced to allocate IRSs to eMBB users, and a puncturing technique is used to assign eMBB resources to URLLC users. Simulation results reveal a superior performance of the proposed scheme over baseline methods, particularly in terms of the eMBB sum data rates and URLLC reliability. Additionally, the proposed algorithm’s sum rate for eMBB users closely approximates that of an exhaustive search (ES) method. The results of our complexity analysis demonstrate that the proposed scheme has a lower computational complexity as compared to the ES scheme.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 3","pages":"1206-1223"},"PeriodicalIF":6.7,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144880611","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}
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