Grover Adaptive Search for Maximum Likelihood Detection of Generalized Spatial Modulation
Abstract
We propose a quantum-assisted solution for the maximum likelihood detection (MLD) of generalized spatial modulation (GSM) signals. Specifically, the MLD of GSM is first formulated as a novel polynomial optimization problem, followed by the application of a quantum algorithm, namely, the Grover adaptive search. The performance in terms of query complexity of the proposed method is evaluated and compared to the classical alternative via a numerical analysis, which reveals that under fault-tolerant quantum computation, the proposed method outperforms the classical solution if the number of data symbols and the constellation size are relatively large.
Cite
@article{arxiv.2408.13531,
title = {Grover Adaptive Search for Maximum Likelihood Detection of Generalized Spatial Modulation},
author = {Kein Yukiyoshi and Taku Mikuriya and Hyeon Seok Rou and Giuseppe Thadeu Freitas de Abreu and Naoki Ishikawa},
journal= {arXiv preprint arXiv:2408.13531},
year = {2024}
}
Comments
5 pages, 4 figures, accepted for presentation at the IEEE 100th Vehicular Technology Conference (VTC2024-Fall)