Modeling of Hybrid Energy Harvesting Communication Systems

被引:27
作者
Altinel, Dogay [1 ]
Kurt, Gunes Karabulut [2 ]
机构
[1] Istanbul Medeniyet Univ, Elect & Elect Engn Dept, TR-34700 Istanbul, Turkey
[2] Istanbul Tech Univ, Elect & Commun Engn Dept, TR-34469 Istanbul, Turkey
来源
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING | 2019年 / 3卷 / 02期
关键词
Energy harvesting; hybrid energy harvesting; energy model; Markov model; Gaussian mixture model; wireless power transfer; battery recharging;
D O I
10.1109/TGCN.2019.2908086
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Energy harvesting is considered as a prominent technology, particularly for low-power wireless nodes. In this paper, we propose the use of hybrid energy harvesting (HEH) utilizing multiple type energy sources and present the modeling of HEH communication systems based on their probabilistic natures. According to our approach, received energy levels of an HEH system for possible combinations of energy arrivals are characterized by using Gaussian mixture models, which are used to determine harvested energy levels. The range of harvested energy is partitioned, and probabilities of partitioning intervals are used to form a finite-state Markov energy channel (FSMEC) model as an energy channel. Similar to the energy arrival, we also include the probabilistic energy consumption of wireless node in this model, depending on multiple application services, by means of the FSMEC model. Thus, we develop an integrated Markov energy model for HEH communication systems corresponding to the energy harvesting and energy consumption profiles. To evaluate the performance of an HEH communication system, we derive the expressions of energy outage, energy shortage, and service loss probabilities analytically. In numerical studies, the derived expressions are verified by matching simulation results, and it is shown that the performance improves significantly with energy source diversity.
引用
收藏
页码:523 / 534
页数:12
相关论文
共 24 条
[11]  
Goldsmith A., 2005, WIRELESS COMMUN
[12]  
Leon-Garcia A., 2008, PROBABILITY STAT RAN
[13]  
Mini R.A., 2002, 4 WORKSHOP COMUNICAO, P23
[14]   Design Optimization and Implementation for RF Energy Harvesting Circuits [J].
Nintanavongsa, Prusayon ;
Muncuk, Ufuk ;
Lewis, David Richard ;
Chowdhury, Kaushik Roy .
IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS, 2012, 2 (01) :24-33
[15]   Energy scavenging for mobile and wireless electronics [J].
Paradiso, JA ;
Starner, T .
IEEE PERVASIVE COMPUTING, 2005, 4 (01) :18-27
[16]  
Rasmussen CE, 2000, ADV NEUR IN, V12, P554
[17]   Finite-state Markov modeling of fading channels [J].
Sadeghi, Parastoo ;
Kennedy, Rodney A. ;
Rapajic, Predrag B. ;
Shams, Ramtin .
IEEE SIGNAL PROCESSING MAGAZINE, 2008, 25 (05) :57-80
[18]   Optimal Energy Management Policies for Energy Harvesting Sensor Nodes [J].
Sharma, Vinod ;
Mukherji, Utpal ;
Joseph, Vinay ;
Gupta, Shrey .
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2010, 9 (04) :1326-1336
[19]  
Ventura J, 2011, 2011 IEEE 22ND INTERNATIONAL SYMPOSIUM ON PERSONAL INDOOR AND MOBILE RADIO COMMUNICATIONS (PIMRC), P2168, DOI 10.1109/PIMRC.2011.6139899
[20]   FINITE-STATE MARKOV CHANNEL - A USEFUL MODEL FOR RADIO-COMMUNICATION CHANNELS [J].
WANG, HS ;
MOAYERI, N .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 1995, 44 (01) :163-171