TY - GEN
T1 - Quantum Annealing for Large MIMO Downlink Vector Perturbation Precoding
AU - Kasi, Srikar
AU - Singh, Abhishek Kumar
AU - Venturelli, Davide
AU - Jamieson, Kyle
N1 - Funding Information:
ACKNOWLEDGEMENTS This research is supported by National Science Foundation (NSF) Awards CNS-1824357 and CNS-1824470. Support from USRA Cycle 3 Research Oppurtunity Program allowed machine time on a D-Wave Quantum Annealer machine hosted at NASA Ames Research Center.
Publisher Copyright:
© 2021 IEEE.
PY - 2021/6
Y1 - 2021/6
N2 - In a multi-user system with multiple antennas at the base station, precoding techniques in the downlink broadcast channel allow users to detect their respective data in a non-cooperative manner. Vector Perturbation Precoding (VPP) is a non-linear variant of transmit-side channel inversion that perturbs user data to achieve full diversity order. While promising, finding an optimal perturbation in VPP is known to be an NP-hard problem, demanding heavy computational support at the base station and limiting the feasibility of the approach to small MIMO systems. This work proposes a radically different processing architecture for the downlink VPP problem, one based on Quantum Annealing (QA), to enable the applicability of VPP to large MIMO systems. Our design reduces VPP to a quadratic polynomial form amenable to QA, then refines the problem coefficients to mitigate the adverse effects of QA hardware noise. We evaluate our proposed QA based VPP (QAVP) technique on a real Quantum Annealing device over a variety of design and machine parameter settings. With existing hardware, QAVP can achieve a BER of 10-4 with 100µs compute time, for a 6 × 6 MIMO system using 64 QAM modulation at 32 dB SNR.
AB - In a multi-user system with multiple antennas at the base station, precoding techniques in the downlink broadcast channel allow users to detect their respective data in a non-cooperative manner. Vector Perturbation Precoding (VPP) is a non-linear variant of transmit-side channel inversion that perturbs user data to achieve full diversity order. While promising, finding an optimal perturbation in VPP is known to be an NP-hard problem, demanding heavy computational support at the base station and limiting the feasibility of the approach to small MIMO systems. This work proposes a radically different processing architecture for the downlink VPP problem, one based on Quantum Annealing (QA), to enable the applicability of VPP to large MIMO systems. Our design reduces VPP to a quadratic polynomial form amenable to QA, then refines the problem coefficients to mitigate the adverse effects of QA hardware noise. We evaluate our proposed QA based VPP (QAVP) technique on a real Quantum Annealing device over a variety of design and machine parameter settings. With existing hardware, QAVP can achieve a BER of 10-4 with 100µs compute time, for a 6 × 6 MIMO system using 64 QAM modulation at 32 dB SNR.
KW - Downlink Precoding
KW - Optimization
KW - Quantum Annealing
KW - Quantum Computation
KW - Vector Perturbation
UR - http://www.scopus.com/inward/record.url?scp=85107927145&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85107927145&partnerID=8YFLogxK
U2 - 10.1109/ICC42927.2021.9500557
DO - 10.1109/ICC42927.2021.9500557
M3 - Conference contribution
AN - SCOPUS:85107927145
T3 - IEEE International Conference on Communications
BT - ICC 2021 - IEEE International Conference on Communications, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Conference on Communications, ICC 2021
Y2 - 14 June 2021 through 23 June 2021
ER -