@Article{cmes.2023.028533,
AUTHOR = {Yingying Chen, Weiqiang Tan, Shidang Li},
TITLE = {Fairness-Aware Harvested Energy Efficiency Algorithm for IRS-Aided Intelligent Sensor Networks with SWIPT},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {137},
YEAR = {2023},
NUMBER = {3},
PAGES = {2675--2691},
URL = {http://www.techscience.com/CMES/v137n3/53733},
ISSN = {1526-1506},
ABSTRACT = {In this paper, a novel fairness-aware harvested energy efficiency-based green transmission scheme for wireless
information and power transfer (SWIPT) aided sensor networks is developed for active beamforming of multiantenna transmitter and passive beamforming at intelligent reflecting surfaces (IRS). By optimizing the active
beamformer assignment at the transmitter in conjunction with the passive beamformer assignment at the IRS, we
aim to maximize the minimum harvested energy efficiency among all the energy receivers (ER) where information
receivers (IR) are bound to the signal-interference-noise-ratio (SINR) and the maximum transmitted power of
the transmitter. To handle the non-convex problem, both semi-definite relaxation (SDR) and block coordinate
descent technologies are exploited. Then, the original problem is transformed into two convex sub-problems which
can be solved via semidefinite programming. Numerical simulation results demonstrate that the IRS and energy
beamformer settings in this paper provide greater system gain than the traditional experimental setting, thereby
improving the fairness-aware harvested energy efficiency of the ER.},
DOI = {10.32604/cmes.2023.028533}
}