TY - GEN
T1 - A Hybrid Classical-Quantum Computing Framework for RIS-Assisted Wireless Network
AU - Ross, Charles
AU - Gradoni, Gabriele
AU - Peng, Zhen
N1 - ACKNOWLEDGMENT The work is supported by U.S. NSF CAREER award, #1750839, ECCS-EPSRC award, #2152617, the Royal Society Industry Fellowship, INF/R2/192066, and the European Union’s Horizon 2020 Industrial leadership project RISE-6G, No. 101017011.
PY - 2023
Y1 - 2023
N2 - Recently, there has been a growing interest in employing reconfigurable intelligent surfaces (RISs) to improve the spectrum and energy efficiency of wireless networks. In RIS-Assisted wireless networks, channel estimation and optimization is a difficult task, particularly for nearly passive RIS devices with low-complexity hardware design. We have proposed a hybrid classical-quantum computing framework that allows for ultra-fast optimization adapting to multipath wireless environments. The onsite optimization of RIS configuration can be performed almost instantaneously using only feedback (received power) at wireless endpoints. The performance of the proposed work is demonstrated in representative wireless propagation scenarios.
AB - Recently, there has been a growing interest in employing reconfigurable intelligent surfaces (RISs) to improve the spectrum and energy efficiency of wireless networks. In RIS-Assisted wireless networks, channel estimation and optimization is a difficult task, particularly for nearly passive RIS devices with low-complexity hardware design. We have proposed a hybrid classical-quantum computing framework that allows for ultra-fast optimization adapting to multipath wireless environments. The onsite optimization of RIS configuration can be performed almost instantaneously using only feedback (received power) at wireless endpoints. The performance of the proposed work is demonstrated in representative wireless propagation scenarios.
KW - 6G
KW - Electromagnetic metamaterials
KW - Ising model
KW - quantum annealing
KW - reconfigurable intelligent surface
KW - wireless communication
UR - http://www.scopus.com/inward/record.url?scp=85168994787&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85168994787&partnerID=8YFLogxK
U2 - 10.1109/NEMO56117.2023.10202166
DO - 10.1109/NEMO56117.2023.10202166
M3 - Conference contribution
AN - SCOPUS:85168994787
T3 - 2023 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization, NEMO 2023
SP - 99
EP - 102
BT - 2023 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization, NEMO 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization, NEMO 2023
Y2 - 28 June 2023 through 30 June 2023
ER -