Pub Date : 2023-11-28DOI: 10.1109/TGCN.2023.3336423
Peishun Yan;Xiaodong Ji;Yulong Zou;Bin Li
This paper considers a typical system composed of multiple energy-constraint users, a destination, and a passive eavesdropper who may intercept confidential information. Each communication time frame is divided into two phases. The first phase is that the energy-constraint users harvest energy from a power beacon. To safeguard the legitimate transmissions, we propose two multiuser scheduling schemes, namely selection combining scheduling (SCS) scheme and switch-and-examine combining scheduling with post-selection (SECSPS) scheme, which only depend on the channel state information of main links spanning from energy-constraint users to the destination. We derive the closed-form expressions of outage probability, intercept probability, and effective secrecy throughput under hardware impairments and channel estimation errors for the SCS and SECSPS schemes. As a baseline, we exploit the system performance for the round-robin scheduling (RRS) scheme. The numerical results verify the correctness of our derivations, demonstrating that the proposed SCS scheme achieves the best performance while the RRS scheme performs the worst in terms of system performance. Furthermore, our proposed SECSPS scheme consumes less computation overhead than the SCS scheme if a suitable threshold is adopted and it requires more computation overhead than the RRS scheme regardless of the threshold.
{"title":"Physical-Layer Security for Energy-Harvesting Multiuser Systems Under Hardware Impairments and Channel Estimation Errors","authors":"Peishun Yan;Xiaodong Ji;Yulong Zou;Bin Li","doi":"10.1109/TGCN.2023.3336423","DOIUrl":"https://doi.org/10.1109/TGCN.2023.3336423","url":null,"abstract":"This paper considers a typical system composed of multiple energy-constraint users, a destination, and a passive eavesdropper who may intercept confidential information. Each communication time frame is divided into two phases. The first phase is that the energy-constraint users harvest energy from a power beacon. To safeguard the legitimate transmissions, we propose two multiuser scheduling schemes, namely selection combining scheduling (SCS) scheme and switch-and-examine combining scheduling with post-selection (SECSPS) scheme, which only depend on the channel state information of main links spanning from energy-constraint users to the destination. We derive the closed-form expressions of outage probability, intercept probability, and effective secrecy throughput under hardware impairments and channel estimation errors for the SCS and SECSPS schemes. As a baseline, we exploit the system performance for the round-robin scheduling (RRS) scheme. The numerical results verify the correctness of our derivations, demonstrating that the proposed SCS scheme achieves the best performance while the RRS scheme performs the worst in terms of system performance. Furthermore, our proposed SECSPS scheme consumes less computation overhead than the SCS scheme if a suitable threshold is adopted and it requires more computation overhead than the RRS scheme regardless of the threshold.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141078776","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 : 2023-11-28DOI: 10.1109/TGCN.2023.3336231
Dimitrios Pliatsios;Alexandros-Apostolos A. Boulogeorgos;Pantelis Angelidis;Angelos Michalas;Panagiotis Sarigiannidis
This paper introduces a novel semi-grant-free non-orthogonal multiple access protocol that ensures reliable massive connectivity of both scheduled and random access devices of diverse data rate (DR) requirements while tripling the network’s capacity. In more detail, the protocol classifies the devices into two categories, namely primary and secondary. Primary devices (PDs) require high-data-rate scheduled or random access with high-transmission probability, and are one-third of the total number of devices, while, the rest, are classified as secondary devices (SDs) and have low-DR requirements as well as access the network in a random fashion. The base-station generates a number of radio resource blocks (RRBs) that is equal to the number of PDs and allocates a primary and two SDs in each RRB. The allocation is based on the requested DRs of the primary and SDs as well as on the transmission probability of the SDs. To prove the feasibility and efficiency of the presented protocol, we conduct a performance analysis that results in the extraction of novel and insightful closed-form expressions for the outage probability and achieved throughput for all devices.
{"title":"A Priority-Based Semi-Grant-Free NOMA: Protocol Design and Performance Analysis","authors":"Dimitrios Pliatsios;Alexandros-Apostolos A. Boulogeorgos;Pantelis Angelidis;Angelos Michalas;Panagiotis Sarigiannidis","doi":"10.1109/TGCN.2023.3336231","DOIUrl":"https://doi.org/10.1109/TGCN.2023.3336231","url":null,"abstract":"This paper introduces a novel semi-grant-free non-orthogonal multiple access protocol that ensures reliable massive connectivity of both scheduled and random access devices of diverse data rate (DR) requirements while tripling the network’s capacity. In more detail, the protocol classifies the devices into two categories, namely primary and secondary. Primary devices (PDs) require high-data-rate scheduled or random access with high-transmission probability, and are one-third of the total number of devices, while, the rest, are classified as secondary devices (SDs) and have low-DR requirements as well as access the network in a random fashion. The base-station generates a number of radio resource blocks (RRBs) that is equal to the number of PDs and allocates a primary and two SDs in each RRB. The allocation is based on the requested DRs of the primary and SDs as well as on the transmission probability of the SDs. To prove the feasibility and efficiency of the presented protocol, we conduct a performance analysis that results in the extraction of novel and insightful closed-form expressions for the outage probability and achieved throughput for all devices.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10330608","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141078754","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 : 2023-11-27DOI: 10.1109/TGCN.2023.3336739
Shiguo Wang;Linzhi Li;Peng Li;Yongjian Zhang;Rukhsana Ruby;Qingyong Deng
To combat the severe path fading between two users/access points and obtain enough signal gain for demodulation, a three-terminal cooperative communication system with a UAV operating as a two-way relay is presented in this paper, and then its optimal energy efficiency is investigated. Specifically, considering the time slot pairing between multiple access (MA) and broadcast (BC) phases, the energy efficiency of the UAV is maximized by optimizing the transmit power of the three terminals and the UAV trajectory jointly. For such a non-convex problem, to obtain its optimal solution, it is decomposed into three subproblems based on the block coordinate descent (BCD) method. Then, after the optimal solutions of the subproblems have been derived based on the successive convex approximation (SCA) techniques, the overall solution of the original optimization problem is obtained in an alternative manner. Simulation results show that the proposed optimization scheme can enhance energy efficiency significantly compared to other existing schemes while considering the reduction system power consumption.
{"title":"Joint Optimization on Energy Efficiency for UAV-Enabled Two-Way Relay Systems","authors":"Shiguo Wang;Linzhi Li;Peng Li;Yongjian Zhang;Rukhsana Ruby;Qingyong Deng","doi":"10.1109/TGCN.2023.3336739","DOIUrl":"https://doi.org/10.1109/TGCN.2023.3336739","url":null,"abstract":"To combat the severe path fading between two users/access points and obtain enough signal gain for demodulation, a three-terminal cooperative communication system with a UAV operating as a two-way relay is presented in this paper, and then its optimal energy efficiency is investigated. Specifically, considering the time slot pairing between multiple access (MA) and broadcast (BC) phases, the energy efficiency of the UAV is maximized by optimizing the transmit power of the three terminals and the UAV trajectory jointly. For such a non-convex problem, to obtain its optimal solution, it is decomposed into three subproblems based on the block coordinate descent (BCD) method. Then, after the optimal solutions of the subproblems have been derived based on the successive convex approximation (SCA) techniques, the overall solution of the original optimization problem is obtained in an alternative manner. Simulation results show that the proposed optimization scheme can enhance energy efficiency significantly compared to other existing schemes while considering the reduction system power consumption.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141078860","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 : 2023-11-22DOI: 10.1109/TGCN.2023.3335342
Ahmad Shahnejat Bushehri;Ashkan Amirnia;Adel Belkhiri;Samira Keivanpour;Felipe Gohring de Magalhães;Gabriela Nicolescu
The widespread use of sensor devices in IoT networks imposes a significant burden on energy consumption at the network’s edge. To address energy concerns, a prompt anomaly detection strategy is required on demand for troubleshooting resource-constrained IoT devices. It enables devices to adapt their configuration according to the dynamic signal quality and transmission settings. However, obtaining accurate energy data from IoT nodes without external devices is unfeasible. This paper proposes a framework for energy anomaly detection of IoT nodes using data transmission analysis. We use a public dataset that contains peer-to-peer IoT communication energy and link quality data. Our framework first utilizes linear regression to analyze and identify the dominant features of data communication for IoT transceivers. Later, a deep neural network modifies the gradient flow to focus on the dominant features. This modification improves the detection accuracy of anomalies by minimizing the associated reconstruction error. Finally, the energy stabilization feedback provides nodes with insight to change their transmission configuration for future communication. The experimental results show that the proposed approach outperforms other unsupervised models in anomalous energy detection. It also proves that redesigning the conventional loss function by enhancing the impact of our dominant features can dramatically improve the reliability of the anomaly detection method.
{"title":"Deep Learning-Driven Anomaly Detection for Green IoT Edge Networks","authors":"Ahmad Shahnejat Bushehri;Ashkan Amirnia;Adel Belkhiri;Samira Keivanpour;Felipe Gohring de Magalhães;Gabriela Nicolescu","doi":"10.1109/TGCN.2023.3335342","DOIUrl":"https://doi.org/10.1109/TGCN.2023.3335342","url":null,"abstract":"The widespread use of sensor devices in IoT networks imposes a significant burden on energy consumption at the network’s edge. To address energy concerns, a prompt anomaly detection strategy is required on demand for troubleshooting resource-constrained IoT devices. It enables devices to adapt their configuration according to the dynamic signal quality and transmission settings. However, obtaining accurate energy data from IoT nodes without external devices is unfeasible. This paper proposes a framework for energy anomaly detection of IoT nodes using data transmission analysis. We use a public dataset that contains peer-to-peer IoT communication energy and link quality data. Our framework first utilizes linear regression to analyze and identify the dominant features of data communication for IoT transceivers. Later, a deep neural network modifies the gradient flow to focus on the dominant features. This modification improves the detection accuracy of anomalies by minimizing the associated reconstruction error. Finally, the energy stabilization feedback provides nodes with insight to change their transmission configuration for future communication. The experimental results show that the proposed approach outperforms other unsupervised models in anomalous energy detection. It also proves that redesigning the conventional loss function by enhancing the impact of our dominant features can dramatically improve the reliability of the anomaly detection method.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10325633","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139715251","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 : 2023-11-21DOI: 10.1109/TGCN.2023.3330253
{"title":"IEEE Communications Society Information","authors":"","doi":"10.1109/TGCN.2023.3330253","DOIUrl":"https://doi.org/10.1109/TGCN.2023.3330253","url":null,"abstract":"","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10325355","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138431227","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 : 2023-11-21DOI: 10.1109/TGCN.2023.3330251
{"title":"IEEE Transactions on Green Communications and Networking","authors":"","doi":"10.1109/TGCN.2023.3330251","DOIUrl":"https://doi.org/10.1109/TGCN.2023.3330251","url":null,"abstract":"","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10325358","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138431122","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 : 2023-11-20DOI: 10.1109/TGCN.2023.3334495
Amin Lotfolahi;Huei-Wen Ferng
A novel cluster-based traffic offloading and user association (UA) algorithm alongside a multi-agent deep reinforcement learning (DRL) based base station (BS) activation mechanism is proposed in this paper. Our design aims to maximize the energy efficiency (EE) of the heterogeneous network (HetNet) while maintaining high quality of service (QoS). By taking advantage of the dense deployment of BSs in a HetNet, a clustering algorithm is first proposed to facilitate traffic offloading among BSs. Then, a multi-agent proximal policy optimization (MAPPO) based DRL algorithm is employed to trigger the BS activation decision based on the current environmental condition. Finally, a UA algorithm is deployed to improve further the (normalized) data rate of all users, known as the (normalized) sum rate. Via simulation, we show that our proposed mechanism can remarkably enhance the EE and excel over the closely related mechanisms. It satisfies the required data rate, improves the sum rate, and exhibits excellent scalability when many BSs are deployed.
{"title":"A Multi-Agent Proximal Policy Optimized Joint Mechanism in mmWave HetNets With CoMP Toward Energy Efficiency Maximization","authors":"Amin Lotfolahi;Huei-Wen Ferng","doi":"10.1109/TGCN.2023.3334495","DOIUrl":"https://doi.org/10.1109/TGCN.2023.3334495","url":null,"abstract":"A novel cluster-based traffic offloading and user association (UA) algorithm alongside a multi-agent deep reinforcement learning (DRL) based base station (BS) activation mechanism is proposed in this paper. Our design aims to maximize the energy efficiency (EE) of the heterogeneous network (HetNet) while maintaining high quality of service (QoS). By taking advantage of the dense deployment of BSs in a HetNet, a clustering algorithm is first proposed to facilitate traffic offloading among BSs. Then, a multi-agent proximal policy optimization (MAPPO) based DRL algorithm is employed to trigger the BS activation decision based on the current environmental condition. Finally, a UA algorithm is deployed to improve further the (normalized) data rate of all users, known as the (normalized) sum rate. Via simulation, we show that our proposed mechanism can remarkably enhance the EE and excel over the closely related mechanisms. It satisfies the required data rate, improves the sum rate, and exhibits excellent scalability when many BSs are deployed.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139715253","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 : 2023-11-15DOI: 10.1109/TGCN.2023.3332773
Qing Xue;Hao Xia;Jiajun Mu;Yongjun Xu;Li Yan;Shaodan Ma
Multi-connectivity and reconfigurable intelligent surface (RIS) are two promising technologies to tackle the challenging blockage issue in millimeter wave (mmWave) communications. Multi-connectivity enables a single user to associate with several mmWave base stations (mBSs) simultaneously, while deploying RIS can construct virtual line-of-sight (LoS) links to bypass obstacles. For dense mmWave networks integrated with multiple RISs, the user association problem that significantly affects system performance by screening out effective and robust communication links is actually a hybrid association problem, consisting of mBS-user association and mBS-RIS-user association. However, this vital association issue has hardly been investigated yet. In this paper, we consider the hybrid association under a user-centric architecture to mitigate the blocking effect, and jointly optimize the power allocation problem between multiple associated links to maximize the achievable sum rate of the user. To effectively solve the formulated optimization problem, which is NP-hard, a series of reformulations, relaxations, and decompositions are introduced. Subsequently, employing Lagrangian duality and multiple-ratio fractional programming, a low-complexity algorithm based on alternating iterations is designed to solve the subproblems of mBS-user association, mBS-RIS-user association, and transmit power allocation. Finally, the effectiveness of the proposed user-centric association algorithm is verified by numerical simulations.
{"title":"User-Centric Association for Dense mmWave Communication Systems With Multi-Connectivity","authors":"Qing Xue;Hao Xia;Jiajun Mu;Yongjun Xu;Li Yan;Shaodan Ma","doi":"10.1109/TGCN.2023.3332773","DOIUrl":"10.1109/TGCN.2023.3332773","url":null,"abstract":"Multi-connectivity and reconfigurable intelligent surface (RIS) are two promising technologies to tackle the challenging blockage issue in millimeter wave (mmWave) communications. Multi-connectivity enables a single user to associate with several mmWave base stations (mBSs) simultaneously, while deploying RIS can construct virtual line-of-sight (LoS) links to bypass obstacles. For dense mmWave networks integrated with multiple RISs, the user association problem that significantly affects system performance by screening out effective and robust communication links is actually a hybrid association problem, consisting of mBS-user association and mBS-RIS-user association. However, this vital association issue has hardly been investigated yet. In this paper, we consider the hybrid association under a user-centric architecture to mitigate the blocking effect, and jointly optimize the power allocation problem between multiple associated links to maximize the achievable sum rate of the user. To effectively solve the formulated optimization problem, which is NP-hard, a series of reformulations, relaxations, and decompositions are introduced. Subsequently, employing Lagrangian duality and multiple-ratio fractional programming, a low-complexity algorithm based on alternating iterations is designed to solve the subproblems of mBS-user association, mBS-RIS-user association, and transmit power allocation. Finally, the effectiveness of the proposed user-centric association algorithm is verified by numerical simulations.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135710823","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 : 2023-11-14DOI: 10.1109/TGCN.2023.3332571
Muddasir Rahim;Georges Kaddoum;Tri Nhu Do
The Industrial Internet of Things (IIoT) enables industries to build large interconnected systems utilizing various technologies that require high data rates. Terahertz (THz) communication is envisioned as a candidate technology for achieving data rates of several terabits-per-second (Tbps). Despite this, establishing a reliable communication link at THz frequencies remains a challenge due to high pathloss and molecular absorption. To overcome these limitations, this paper proposes using intelligent reconfigurable surfaces (IRSs) with THz communications to enable future smart factories for the IIoT. In this paper, we formulate the power allocation and joint IIoT device and IRS association (JIIA) problem, which is a mixed-integer nonlinear programming (MINLP) problem. Furthermore, the JIIA problem aims to maximize the sum rate with imperfect channel state information (CSI). To address this non-deterministic polynomial-time hard (NP-hard) problem, we decompose the problem into multiple sub-problems, which we solve iteratively. Specifically, we propose a Gale-Shapley algorithm-based JIIA solution to obtain stable matching between uplink and downlink IRSs. We validate the proposed solution by comparing the Gale-Shapley-based JIIA algorithm with exhaustive search (ES), greedy search (GS), and random association (RA) with imperfect CSI. The complexity analysis shows that our algorithm is more efficient than the ES.
{"title":"Joint Devices and IRSs Association for Terahertz Communications in Industrial IoT Networks","authors":"Muddasir Rahim;Georges Kaddoum;Tri Nhu Do","doi":"10.1109/TGCN.2023.3332571","DOIUrl":"10.1109/TGCN.2023.3332571","url":null,"abstract":"The Industrial Internet of Things (IIoT) enables industries to build large interconnected systems utilizing various technologies that require high data rates. Terahertz (THz) communication is envisioned as a candidate technology for achieving data rates of several terabits-per-second (Tbps). Despite this, establishing a reliable communication link at THz frequencies remains a challenge due to high pathloss and molecular absorption. To overcome these limitations, this paper proposes using intelligent reconfigurable surfaces (IRSs) with THz communications to enable future smart factories for the IIoT. In this paper, we formulate the power allocation and joint IIoT device and IRS association (JIIA) problem, which is a mixed-integer nonlinear programming (MINLP) problem. Furthermore, the JIIA problem aims to maximize the sum rate with imperfect channel state information (CSI). To address this non-deterministic polynomial-time hard (NP-hard) problem, we decompose the problem into multiple sub-problems, which we solve iteratively. Specifically, we propose a Gale-Shapley algorithm-based JIIA solution to obtain stable matching between uplink and downlink IRSs. We validate the proposed solution by comparing the Gale-Shapley-based JIIA algorithm with exhaustive search (ES), greedy search (GS), and random association (RA) with imperfect CSI. The complexity analysis shows that our algorithm is more efficient than the ES.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135662691","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 : 2023-11-14DOI: 10.1109/TGCN.2023.3332494
Peng Qin;Guoming Tang;Yang Fu;Yi Wang
The mobile network operators are upgrading their network facilities and shifting to the 5G era at an unprecedented pace. The huge operating expense (OPEX), mainly the energy consumption cost, has become the major concern of the operators. In this work, we investigate the energy cost-saving potential by transforming the backup batteries of base stations (BSs) to a distributed battery energy storage system (BESS). Specifically, to minimize the total energy cost, we model the distributed BESS discharge/charge scheduling as an optimization problem by incorporating comprehensive practical considerations. Then, considering the dynamic BS power demands in practice, we propose a multi-agent deep reinforcement learning (MADRL) based approach to make distributed BESS scheduling decisions in real-time. Particularly, QMIX framework is leveraged to learn the partial policy of each agent in the training phase; while in the execution phase, each BS can make scheduling decisions based on local information. The experiments using real-world BS deployment and traffic load data demonstrate that with our QMIX-based distributed BESS scheduling, the peak power demand charge of BSs can be reduced by more than 26.59%, and the yearly OPEX saving for 2282 5G BSs could reach up to U.S. ${$}$ 196,000.
{"title":"Distributed BESS Scheduling for Power Demand Reshaping in 5G and Beyond Networks","authors":"Peng Qin;Guoming Tang;Yang Fu;Yi Wang","doi":"10.1109/TGCN.2023.3332494","DOIUrl":"10.1109/TGCN.2023.3332494","url":null,"abstract":"The mobile network operators are upgrading their network facilities and shifting to the 5G era at an unprecedented pace. The huge operating expense (OPEX), mainly the energy consumption cost, has become the major concern of the operators. In this work, we investigate the energy cost-saving potential by transforming the backup batteries of base stations (BSs) to a distributed battery energy storage system (BESS). Specifically, to minimize the total energy cost, we model the distributed BESS discharge/charge scheduling as an optimization problem by incorporating comprehensive practical considerations. Then, considering the dynamic BS power demands in practice, we propose a multi-agent deep reinforcement learning (MADRL) based approach to make distributed BESS scheduling decisions in real-time. Particularly, QMIX framework is leveraged to learn the partial policy of each agent in the training phase; while in the execution phase, each BS can make scheduling decisions based on local information. The experiments using real-world BS deployment and traffic load data demonstrate that with our QMIX-based distributed BESS scheduling, the peak power demand charge of BSs can be reduced by more than 26.59%, and the yearly OPEX saving for 2282 5G BSs could reach up to U.S.\u0000<inline-formula> <tex-math>${$}$ </tex-math></inline-formula>\u0000196,000.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135661087","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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