TY - JOUR
T1 - Intelligent Reflecting Surface Based Backscatter Communication for Data Offloading
AU - Xu, Sai
AU - Du, Yanan
AU - Liu, Jiajia
AU - Li, Jingtao
N1 - Publisher Copyright:
© 1972-2012 IEEE.
PY - 2022/6/1
Y1 - 2022/6/1
N2 - This paper investigates intelligent reflecting surface based backscatter communication (IRS-BackCom), in order to realize computational task offloading of energy-constrained mobile edge computing network in a self-sustainable manner. Specifically, the system operation is divided into two phases. In the first one, the ambient signal energy from a power beacon (PB) either provides the energy supply of local computing and energy harvesting circuits, or flows into the energy storage, when reaching the IRS. In the second one, the stored energy is used to enable IRS-BackCom for partial computational data offloading and energize local computing circuit. Based on this, the maximization problem of sum computational bits is formulated. By jointly optimizing the beamforming vector at the PB, the backscatter matrix at the IRS, the time scheduling of two-phase process, as well as the time of local computing, sum computational bits are maximized. In addition, this paper proposes element clustering to realize BackCom, so as to reduce the control and computation complexity of IRS. According to different operating mechanisms, two cluster operation modes are considered, namely independent cluster operation mode and joint cluster operation mode. Simulation results demonstrate the achievable sum computational bits by the proposed IRS-BackCom schemes.
AB - This paper investigates intelligent reflecting surface based backscatter communication (IRS-BackCom), in order to realize computational task offloading of energy-constrained mobile edge computing network in a self-sustainable manner. Specifically, the system operation is divided into two phases. In the first one, the ambient signal energy from a power beacon (PB) either provides the energy supply of local computing and energy harvesting circuits, or flows into the energy storage, when reaching the IRS. In the second one, the stored energy is used to enable IRS-BackCom for partial computational data offloading and energize local computing circuit. Based on this, the maximization problem of sum computational bits is formulated. By jointly optimizing the beamforming vector at the PB, the backscatter matrix at the IRS, the time scheduling of two-phase process, as well as the time of local computing, sum computational bits are maximized. In addition, this paper proposes element clustering to realize BackCom, so as to reduce the control and computation complexity of IRS. According to different operating mechanisms, two cluster operation modes are considered, namely independent cluster operation mode and joint cluster operation mode. Simulation results demonstrate the achievable sum computational bits by the proposed IRS-BackCom schemes.
KW - Backscatter communication (BackCom)
KW - Element clustering
KW - Energy harvesting (EH)
KW - Intelligent reflecting surface (IRS)
KW - Mobile edge computing (MEC)
UR - http://www.scopus.com/inward/record.url?scp=85129577635&partnerID=8YFLogxK
U2 - 10.1109/TCOMM.2022.3170629
DO - 10.1109/TCOMM.2022.3170629
M3 - 文章
AN - SCOPUS:85129577635
SN - 0090-6778
VL - 70
SP - 4211
EP - 4221
JO - IEEE Transactions on Communications
JF - IEEE Transactions on Communications
IS - 6
ER -