aiqbench analysis
This research explores using neutral-atom quantum computing platforms to solve NP-hard resource allocation problems in NOMA wireless networks, specifically by mapping the maximum access problem onto Rydberg atom arrays. By reformulating the task as a maximum independent set problem, the study leverages physical blockade constraints to handle complex combinatorial challenges like user clustering and power allocation that are difficult for classical systems. The numerical results suggest this approach offers a viable pathway for optimizing large-scale communication networks where computational complexity exceeds current classical limits.
Neutral-Atom-based Quantum Optimization for Resource Allocation in NOMA Networks
arXiv:2609.26556v1 Announce Type: new Abstract: In wireless communication networks, many resource optimization problems are nondeterministic polynomial-time hard (NP-hard) due to their combinatorial nature and high computational complexity. Recently, neutral-atom-based quantum computing has emerged as a promising platform for efficiently solving such problems by leveraging quantum superposition and entanglement. However, its application to wireless communication optimization problems remains largely unexplored. In this paper, we investigate the use of neutral-atom quantum platforms to solve the maximum access problem (MAP), formulated as a mixed-integer programming task that jointly considers admission control, user clustering, channel assignment, and power allocation in a non-orthogonal multiple access (NOMA)-enabled uplink network. To reduce the computational burden, the MAP is equivalently reformulated as a maximum independent set (MIS) problem in graph theory. This reformulation enables the use of the neutral atom platform based on Rydberg atom arrays, where the MIS problem is naturally encoded into the physical geometry and blockade constraints of the quantum system. Numerical results demonstrate the feasibility and potential of this approach for addressing large-scale wireless resource optimization problems.
Abstract:In wireless communication networks, many resource optimization problems are nondeterministic polynomial-time hard (NP-hard) due to their combinatorial nature and high computational complexity. Recently, neutral-atom-based quantum computing has emerged as a promising platform for efficiently solving such problems by leveraging quantum superposition and entanglement. However, its application to wireless communication optimization problems remains largely unexplored. In this paper, we investigate the use of neutral-atom quantum platforms to solve the maximum access problem (MAP), formulated as a mixed-integer programming task that jointly considers admission control, user clustering, channel assignment, and power allocation in a non-orthogonal multiple access (NOMA)-enabled uplink network. To reduce the computational burden, the MAP is equivalently reformulated as a maximum independent set (MIS) problem in graph theory. This reformulation enables the use of the neutral atom platform based on Rydberg atom arrays, where the MIS problem is naturally encoded into the physical geometry and blockade constraints of the quantum system. Numerical results demonstrate the feasibility and potential of this approach for addressing large-scale wireless resource optimization problems.
Artificial Intelligence (cs.AI); Information Theory (cs.IT)
arXiv:2609.26556 [cs.AI]
(or arXiv:2609.26556v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2609.26556 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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Full text under the publisher's open licence · 265 words
