Modeling and Analysis of Energy Harvesting and Smart Grid-Powered Wireless Communication Networks: A Contemporary Survey

被引:102
作者
Hu, Shuyan [1 ]
Chen, Xiaojing [2 ]
Ni, Wei [3 ]
Wang, Xin [4 ]
Hossain, Ekram [5 ]
机构
[1] Fudan Univ, Sch Informat Sci & Technol, State Key Lab ASIC & Syst, Shanghai 200433, Peoples R China
[2] Shanghai Univ, Shanghai Inst Adv Commun & Data Sci, Shanghai 200444, Peoples R China
[3] Commonwealth Sci & Ind Res Org, Data61, Sydney, NSW 2122, Australia
[4] Fudan Univ, Shanghai Inst Adv Commun & Data Sci, State Key Lab ASIC & Syst, Dept Commun Sci & Engn, Shanghai 200433, Peoples R China
[5] Univ Manitoba, Dept Elect & Comp Engn, Winnipeg, MB R3T 5V6, Canada
来源
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING | 2020年 / 4卷 / 02期
基金
中国国家自然科学基金; 加拿大自然科学与工程研究理事会;
关键词
5G/B5G communication networks; energy harvesting; smart grid; energy redistribution and trading; optimization techniques; NONORTHOGONAL MULTIPLE-ACCESS; EFFICIENT RESOURCE-ALLOCATION; UNMANNED AERIAL VEHICLES; GREEN CELLULAR NETWORKS; PROXIMAL BUNDLE METHODS; BURSTY DATA PACKETS; TRAJECTORY DESIGN; PERFORMANCE ANALYSIS; CONDITIONAL VALUE; CHARGING STATION;
D O I
10.1109/TGCN.2020.2988270
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
The advancements in smart power grid and the advocation of "green communications" have inspired the wireless communication networks to harness energy from ambient environments and operate in an energy-efficient manner for economic and ecological benefits. This article presents a contemporary review of recent breakthroughs on the utilization, redistribution, trading and planning of energy harvested in future wireless networks interoperating with smart grids. This article starts with classical models of renewable energy harvesting technologies. We embark on constrained operation and optimization of different energy harvesting wireless systems, such as point-to-point, multipoint-to-point, multipoint-to-multipoint, multi-hop, and multi-cell systems. We also review wireless power and information transfer technologies which provide a special implementation of energy harvesting wireless communications. A significant part of the article is devoted to the redistribution of redundant (unused) energy harvested within cellular networks, the energy planning under dynamic pricing when smart grids are in place, and two-way energy trading between cellular networks and smart grids. Applications of different optimization tools, such as convex optimization, Lagrangian dual-based method, subgradient method, and Lyapunov-based online optimization, are compared. This article also collates the potential applications of energy harvesting techniques in emerging (or upcoming) 5G/B5G communication systems. It is revealed that an effective redistribution and two-way trading of energy can significantly reduce the electricity bills of wireless service providers and decrease the consumption of brown energy. A list of interesting research directions are provided, requiring further investigation.
引用
收藏
页码:461 / 496
页数:36
相关论文
共 297 条
[41]   MIMO Precoding for Networked Control Systems with Energy Harvesting Sensors [J].
Cai, Songfu ;
Lau, Vincent K. N. .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2016, 64 (17) :4469-4478
[42]   Optimal Cloud Computing Resource Allocation for Demand Side Management in Smart Grid [J].
Cao, Zijian ;
Lin, Jin ;
Wan, Can ;
Song, Yonghua ;
Zhang, Yi ;
Wang, Xiaohui .
IEEE TRANSACTIONS ON SMART GRID, 2017, 8 (04) :1943-1955
[43]   Supervised learning of semantic classes for image annotation and retrieval [J].
Carneiro, Gustavo ;
Chan, Antoni B. ;
Moreno, Pedro J. ;
Vasconcelos, Nuno .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2007, 29 (03) :394-410
[44]   A Dynamic Programming Algorithm for High-Level Task Scheduling in Energy Harvesting IoT [J].
Caruso, Antonio ;
Chessa, Stefano ;
Escolar, Soledad ;
del Toro, Xavier ;
Carlos Lopez, Juan .
IEEE INTERNET OF THINGS JOURNAL, 2018, 5 (03) :2234-2248
[45]   Dynamic Base Station Operation in Large-Scale Green Cellular Networks [J].
Che, Yue Ling ;
Duan, Lingjie ;
Zhang, Rui .
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2016, 34 (12) :3127-3141
[46]   Learning and Management for Internet of Things: Accounting for Adaptivity and Scalability [J].
Chen, Tianyi ;
Barbarossa, Sergio ;
Wang, Xin ;
Giannakis, Georgios B. ;
Zhang, Zhi-Li .
PROCEEDINGS OF THE IEEE, 2019, 107 (04) :778-796
[47]   Stochastic Averaging for Constrained Optimization With Application to Online Resource Allocation [J].
Chen, Tianyi ;
Mokhtari, Aryan ;
Wang, Xin ;
Ribeiro, Alejandro ;
Giannakis, Georgios B. .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2017, 65 (12) :3078-3093
[48]   Multi-Timescale Online Optimization of Network Function Virtualization for Service Chaining [J].
Chen, Xiaojing ;
Ni, Wei ;
Chen, Tianyi ;
Collings, Iain B. ;
Wang, Xin ;
Liu, Ren Ping ;
Giannakis, Georgios B. .
IEEE TRANSACTIONS ON MOBILE COMPUTING, 2019, 18 (12) :2899-2912
[49]   Automated Function Placement and Online Optimization of Network Functions Virtualization [J].
Chen, Xiaojing ;
Ni, Wei ;
Collings, Iain B. ;
Wang, Xin ;
Xu, Shugong .
IEEE TRANSACTIONS ON COMMUNICATIONS, 2019, 67 (02) :1225-1237
[50]   REAL-TIME ENERGY TRADING AND FUTURE PLANNING FOR FIFTH GENERATION WIRELESS COMMUNICATIONS [J].
Chen, Xiaojing ;
Ni, Wei ;
Chen, Tianyi ;
Collings, Iain B. ;
Wang, Xin ;
Giannakis, Georgios B. .
IEEE WIRELESS COMMUNICATIONS, 2017, 24 (04) :24-30