1.
Winter, Samuel; Zhang, Yangyishi; Zheng, Gan; Hanzo, Lajos
A Lattice-Reduction Aided Vector Perturbation Precoder Relying on Quantum Annealing Journal Article
In: IEEE Wireless Communications Letters, vol. 13, no. 5, pp. 1225–1229, 2024, ISSN: 2162-2345.
Abstract | Links | BibTeX | Tags: Annealing, downlink precoding, Hardware, Lattices, MIMO, Perturbation methods, Quantum annealing, Qubit, Symbols, vector perturbation
@article{winter_lattice-reduction_2024,
title = {A Lattice-Reduction Aided Vector Perturbation Precoder Relying on Quantum Annealing},
author = {Samuel Winter and Yangyishi Zhang and Gan Zheng and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/10436537},
doi = {10.1109/LWC.2024.3365874},
issn = {2162-2345},
year = {2024},
date = {2024-05-01},
urldate = {2025-10-08},
journal = {IEEE Wireless Communications Letters},
volume = {13},
number = {5},
pages = {1225–1229},
abstract = {Quantum annealing (QA) is proposed for vector perturbation precoding (VPP) in multiple input multiple output (MIMO) communications systems. The mathematical framework of VPP is presented, outlining the problem formulation and the benefits of lattice reduction algorithms. Lattice reduction aided quantum vector perturbation (LRAQVP) is designed by harnessing physical quantum hardware, and the optimization of hardware parameters is discussed. We observe a 5dB gain over lattice reduction zero forcing precoding (LRZFP), which behaves similarly to a quantum annealing algorithm operating without a lattice reduction stage. The proposed algorithm is also shown to approach the performance of a sphere encoder, which exhibits an exponentially escalating complexity.},
keywords = {Annealing, downlink precoding, Hardware, Lattices, MIMO, Perturbation methods, Quantum annealing, Qubit, Symbols, vector perturbation},
pubstate = {published},
tppubtype = {article}
}
Quantum annealing (QA) is proposed for vector perturbation precoding (VPP) in multiple input multiple output (MIMO) communications systems. The mathematical framework of VPP is presented, outlining the problem formulation and the benefits of lattice reduction algorithms. Lattice reduction aided quantum vector perturbation (LRAQVP) is designed by harnessing physical quantum hardware, and the optimization of hardware parameters is discussed. We observe a 5dB gain over lattice reduction zero forcing precoding (LRZFP), which behaves similarly to a quantum annealing algorithm operating without a lattice reduction stage. The proposed algorithm is also shown to approach the performance of a sphere encoder, which exhibits an exponentially escalating complexity.