Power Allocation for an Energy Harvesting Transmitter with Hybrid Energy Sources

被引:66
作者
Ahmed, Imtiaz [1 ]
Ikhlef, Aissa [1 ]
Ng, Derrick Wing Kwan [1 ]
Schober, Robert [1 ]
机构
[1] Univ British Columbia, Dept Elect & Comp Engn, Vancouver, BC V6T 1Z4, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Energy harvesting; hybrid energy supply; power allocation; convex optimization; dynamic programming; COGNITIVE RADIO SYSTEMS; WIRELESS;
D O I
10.1109/TWC.2013.111013.130215
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this work, we consider a point-to-point communication link where the transmitter has a hybrid supply of energy. Specifically, the hybrid energy is supplied by a constant energy source and an energy harvester, which harvests energy from its surrounding environment and stores it in a battery which suffers from energy leakage. Our goal is to minimize the power consumed by the constant energy source for transmission of a given amount of data in a given number of time intervals. Two scenarios are considered for packet arrival. In the first scenario, we assume that all data packets have arrived before transmission begins, whereas in the second scenario, we assume that data packets are arriving during the course of data transmission. For both scenarios, we propose an optimal offline transmit power allocation scheme which provides insight into how to efficiently consume the energy supplied by the constant energy source and the energy harvester. For offline power allocation, we assume that causal and non-causal information regarding the channel and the amount of harvested energy is available a priori. For optimal online power allocation, we adopt a stochastic dynamic programming (DP) approach for both considered scenarios. For online power allocation, only causal information regarding the channel and the amount of harvested energy is assumed available. Due to the inherent high complexity of DP, we propose suboptimal online algorithms which are appealing because of their low complexity. Simulation results reveal that the offline scheme performs best among all considered schemes and the suboptimal online scheme provides a good performance-complexity tradeoff.
引用
收藏
页码:6255 / 6267
页数:13
相关论文
共 21 条
  • [1] Ahmed I., P 2012 IEEE VEH TECH
  • [2] Bertsekas D. P., 1995, Dynamic programming and optimal control, V1
  • [3] Boyd S., 2004, CONVEX OPTIMIZATION, VFirst, DOI DOI 10.1017/CBO9780511804441
  • [4] Fettweis G. P., P 2008 IEEE INT C AC
  • [5] Gurakan B., 2012 IEEE INT S INF
  • [6] Energy-Efficient Power Allocation in OFDM-Based Cognitive Radio Systems: A Risk-Return Model
    Hasan, Ziaul
    Bansal, Gaurav
    Hossain, Ekram
    Bhargava, Vijay K.
    [J]. IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2009, 8 (12) : 6078 - 6088
  • [7] Optimal Energy Allocation for Wireless Communications With Energy Harvesting Constraints
    Ho, Chin Keong
    Zhang, Rui
    [J]. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2012, 60 (09) : 4808 - 4818
  • [8] Throughput Maximization for the Gaussian Relay Channel with Energy Harvesting Constraints
    Huang, Chuan
    Zhang, Rui
    Cui, Shuguang
    [J]. IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2013, 31 (08) : 1469 - 1479
  • [9] Cross-layer scheduling and power control combined with adaptive modulation for wireless ad hoc networks
    Huang, Wei Lan
    Ben Letaief, Khaled
    [J]. IEEE TRANSACTIONS ON COMMUNICATIONS, 2007, 55 (04) : 728 - 739
  • [10] Transmission with Energy Harvesting Nodes in Fading Wireless Channels: Optimal Policies
    Ozel, Omur
    Tutuncuoglu, Kaya
    Yang, Jing
    Ulukus, Sennur
    Yener, Aylin
    [J]. IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2011, 29 (08) : 1732 - 1743