Online Joint Optimization of Power and Modulation in Energy Harvesting Communication Systems

LEI Weijia; SUN Jialin; XIE Xianzhong; LEI Hongjiang

doi:10.11999/JEIT210145

Volume 44 Issue 3

Mar. 2022

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LEI Weijia, SUN Jialin, XIE Xianzhong, LEI Hongjiang. Online Joint Optimization of Power and Modulation in Energy Harvesting Communication Systems[J]. Journal of Electronics & Information Technology, 2022, 44(3): 1024-1033. doi: 10.11999/JEIT210145

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LEI Weijia, SUN Jialin, XIE Xianzhong, LEI Hongjiang. Online Joint Optimization of Power and Modulation in Energy Harvesting Communication Systems[J]. Journal of Electronics & Information Technology, 2022, 44(3): 1024-1033. doi: 10.11999/JEIT210145

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Online Joint Optimization of Power and Modulation in Energy Harvesting Communication Systems

doi: 10.11999/JEIT210145

LEI Weijia^{1, 2},
SUN Jialin^{1, 2
,
,},
XIE Xianzhong³,
LEI Hongjiang¹

1.
School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2.
Chongqing Key Laboratory of Mobile Communications Technology, Chongqing 400065, China
3.
School of Optoelectronic Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Funds: The National Natural Science Foundation of China (61971080, 61471076), The Key Project of Science and Technology Research of Chongqing Education Commission (KJZD-M201900602)

Received Date: 2021-02-18
Accepted Date: 2021-11-05
Rev Recd Date: 2021-10-20

Available Online: 2021-11-11

Publish Date: 2022-03-28

Abstract

Abstract

For a point-to-point energy harvesting wireless communication system equipped with energy harvesting devices at the source node, to maximize the long-term average transmission rate, an online power control and adaptive modulation joint optimization strategy based on Lyapunov optimization framework is proposed. Due to the randomness of the energy arrival and the channel state, the optimization problem is a stochastic optimization problem. By using Lyapunov optimization framework, the long-term optimization problem under the constraints of battery operation and available energy is transformed into a joint optimization problem of the transmission power, the modulation mode and the frame length to minimize the virtual queue drift-plus-penalty" per time slot. The proposed algorithm only dependes on the current channel state and the battery state. The simulation results show that the proposed algorithm can effectively utilize the harvested energy and adapt to the channel changes. The long-term average actual achievable information transmission rate is significantly better than the greedy and the half-power algorithm. Compared with the offline water filling algorithm and other comparison algorithms, both which aim at maximizing the channel capacity, the proposed algorithm also can achieve a higher actual transmission rate.
- Energy harvesting,
- Power control,
- Adaptive modulation,
- Lyapunov optimization

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References(15)

References

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