Energy Efficiency Optimization for OFDM Based 5G Wireless Networks With Simultaneous Wireless Information and Power Transfer | Zendy

Weidang Lu | Zendy; Shanzhen Fang | Zendy; Su Hu | Zendy; Xin Liu | Zendy; Bo Li | Zendy; Zhenyu Na | Zendy; Yi Gong | Zendy

Open Access

Energy Efficiency Optimization for OFDM Based 5G Wireless Networks With Simultaneous Wireless Information and Power Transfer

Author(s) -

Weidang Lu,

Shanzhen Fang,

Su Hu,

Xin Liu,

Bo Li,

Zhenyu Na,

Yi Gong

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2883555

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

In 5G wireless networks, the system capacity and the number of users will be significantly increased. However, the energy consumed for the communication will also be increased, which results in low system energy efficiency. Simultaneous wireless information and power transfer (SWIPT) can enable the user to perform energy harvesting from the radio-frequency signals parallel with the information decoding, which can effectively improve the system energy efficiency. In this paper, we study the energy efficiency optimization problem for the orthogonal frequency-division multiplexing-based 5G wireless networks with SWIPT, in which the subcarrier and power allocation are jointly optimized to maximize the system energy efficiency for single user and multiple user cases. For those two cases, through mathematical transforming, we use the Dinkelbach iterative method and the Lagrange dual method to solve the non-convex energy efficiency optimization problem. Simulation results show that compared with other algorithms, our proposed algorithm can achieve higher energy efficiency.

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