Abstract
This paper considers a SWIPT network in which an
access point (AP) serves multiple information decoding receivers
(IDRs) and energy harvesting receivers (EHRs) assisted by several
dynamically controlled reconfigurable intelligent surfaces (RIS).
An energy efficiency (EE) maximization problem is formulated by
the joint optimization of the transmit beamforming, artificial
noise (AN) covariance, the passive beamforming at the RISs, and
the RIS on/off control mechanism. Due to the non-convexity of the
problem, semi-definite relaxation (SDR) is utilized to simplify the
problem. A practical solution based on alternation optimization is
proposed to obtain the suboptimal solution. Furthermore, a lowcomplexity
greedy search method is proposed for the RIS on/off
control. Simulation results show that the EE is significantly
enhanced by employing dynamic control of multiple RIS with AN.
In addition, the effect of increasing the circuit power and the
number of RISs can be harmful to the system-wide EE.
access point (AP) serves multiple information decoding receivers
(IDRs) and energy harvesting receivers (EHRs) assisted by several
dynamically controlled reconfigurable intelligent surfaces (RIS).
An energy efficiency (EE) maximization problem is formulated by
the joint optimization of the transmit beamforming, artificial
noise (AN) covariance, the passive beamforming at the RISs, and
the RIS on/off control mechanism. Due to the non-convexity of the
problem, semi-definite relaxation (SDR) is utilized to simplify the
problem. A practical solution based on alternation optimization is
proposed to obtain the suboptimal solution. Furthermore, a lowcomplexity
greedy search method is proposed for the RIS on/off
control. Simulation results show that the EE is significantly
enhanced by employing dynamic control of multiple RIS with AN.
In addition, the effect of increasing the circuit power and the
number of RISs can be harmful to the system-wide EE.
Original language | English |
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Title of host publication | 2023 IEEE Virtual Conference on Communications (VCC) |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Publication status | Accepted/In press - 24 Oct 2023 |
Event | 2023 IEEE Virtual Conference on Communications (VCC) - Virtual, Beijing, China Duration: 28 Nov 2023 → 30 Nov 2023 https://www.aconf.org/conf_192685.html |
Conference
Conference | 2023 IEEE Virtual Conference on Communications (VCC) |
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Abbreviated title | IEEE VCC 2023 |
Country/Territory | China |
City | Beijing |
Period | 28/11/23 → 30/11/23 |
Internet address |