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arXiv:2609.26556

Neutral-Atom-based Quantum Optimization for Resource Allocation in NOMA Networks

Patatchona Keyela, Remon A. Polus, Soumaya Cherkaoui, Ola Suleiman Ahmad

Published Sep 22, 2026• 0 citations
arXivHTMLPDF

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.

DOI
10.48550/arxiv.2609.26556

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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.
Resource management in next-generation wireless communication networks poses substantial computational challenges due to its combinatorial structure and mixed discrete–continuous nature. Many such problems are NP-hard (non-deterministic polynomial-time hard), rendering conventional optimization techniques computationally demanding and often impractical for large-scale deployments. Recent advances in neutral atom quantum computing have demonstrated innovative potential for solving combinatorial optimization problems through graph-based formulations. However, their application to wireless resource management remains largely unexplored. This paper investigates the use of neutral atom quantum processors to address the maximum access problem (MAP) in uplink non-orthogonal multiple access (NOMA)-enabled non-terrestrial networks (NTNs). The MAP is first formulated as a large-scale mixed-integer optimization problem that jointly captures admission control, user clustering, channel assignment, and power allocation under signal-to-interference-plus-noise ratio (SINR) constraints, while accounting for imperfect successive interference cancellation (SIC) at the receiver. To enable hardware-aligned quantum implementation, the problem is transformed into a maximum independent set (MIS) problem over a conflict graph. The resulting graph structure is compatible with the operational principles of neutral atom quantum hardware, allowing direct mapping onto Rydberg atom arrays via blockade-induced interactions. Numerical evaluations assess admission performance, graph complexity, and computational behavior, highlighting the effectiveness of the proposed neutral atom-based framework for solving such graph-theoretic problems. By integrating quantum combinatorial optimization into wireless resource management, this work demonstrates a hardware-aligned mapping for NOMA-enabled NTN resource allocation and provides proof-of-concept validation on a current neutral atom processor, showcasing the potential of neutral atom quantum processors for addressing optimization problems in future 6G and beyond networks.
In this paper, we propose a novel uplink Hybrid Non-Orthogonal Multiple Access (NOMA) architecture assisted by Rydberg Atomic Quantum Receivers (RAQRs) to improve energy efficiency by addressing the physical constraints of atomic sensing. We formulate a joint optimization problem encompassing phase measurements and multi-user power allocation to minimize the total transmit power. This problem is particularly challenging due to the non-linear amplitude-only observations of atomic vapor cells. To decomposes the resulting non-convexity, we develop a hierarchical three-layer decomposition optimization framework that systematically decouples the global problem. The inner layer employs a customized Expectation Maximization-Gerchberg-Saxton (EM-GS) algorithm to resolve phase ambiguity and estimate equivalent channel gains. The middle layer derives closed-form optimal power allocation solutions via Karush-Kuhn-Tucker (KKT) conditions. The outer layer utilizes linear Minimum Mean Square Error (MMSE) detection for high-reliability signal recovery. Simulation results demonstrate the superiority of the proposed framework over conventional RF-based Hybrid NOMA. Notably, the atomic architecture achieves approximately a 93% reduction in total power consumption compared to Orthogonal Multiple Access (OMA) baselines while maintaining strict backward compatibility, thereby laying a solid foundation for practical deployment in next-generation green communication networks.
We describe and analyze an architecture for quantum optimization to solve maximum independent set (MIS) problems using neutral atom arrays trapped in optical tweezers. Optimizing independent sets is one of the paradigmatic, NP-hard problems in computer science. Our approach is based on coherent manipulation of atom arrays via the excitation into Rydberg atomic states. Specifically, we show that solutions of MIS problems can be efficiently encoded in the ground state of interacting atoms in 2D arrays by utilizing the Rydberg blockade mechanism. By studying the performance of leading classical algorithms, we identify parameter regimes, where computationally hard instances can be tested using near-term experimental systems. Practical implementations of both quantum annealing and variational quantum optimization algorithms beyond the adiabatic principle are discussed.
Nash equilibria are crucial for understanding game behavior and systems in economics, physics, biology, and computer science. A significant application arises from the connection between Nash equilibria and optimization problems . However, finding Nash equilibria is challenging due to its NP-Hard complexity, specifically within the PPAD class. By exploiting the correspondence between Maximum Independent Sets (MIS) and Nash equilibria on unit-disk graphs, we map these problems onto the ground state configurations of Rydberg atom arrays. Simulations show the effectiveness of this quantum method, highlighting its potential for solving complex problems in game theory.
To support the rapid proliferation of IoT devices, non-uniform multiple access (NOMA) admission control appears as a promising technology. Indeed, through spectrum reuse, it allows more devices to communicate than the traditional orthogonal frequency-division multiple access scheme of 4G. Previous research has shown that the NOMA allocation problem can be formulated into a maximum independent set problem, which is NP-hard. Recent advances in quadratic unconstrained binary optimization (QUBO) solvers show promise in their capability to solve this kind of allocation problems efficiently. We explore various QUBO formulations to determine which is best-suited for the high-frequency requirements of the NOMA allocation problem.
In the past years, many quantum algorithms have been proposed to tackle hard combinatorial problems. These algorithms, which have been studied in depth in complexity theory, are at the heart of many industrial applications. In particular, the Maximum Independent Set (MIS) is a known NP-hard problem that can be naturally encoded in Rydberg atom arrays. By representing a graph with an ensemble of neutral atoms one can leverage Rydberg dynamics to naturally encode the constraints and the solution to MIS. However, the classes of graphs that can be directly mapped node-to-atom on such devices are limited to Unit-Disk graphs. In this setting, the inherent locality of the graphs can be leveraged by classical polynomial-time approximation schemes (PTAS) that guarantee an ε-approximate solution. In this work, we present a deterministic and polynomial-time construction to embed a large family of non-local graphs in 3D atomic arrays. This construction is a first crucial step towards tackling combinatorial tasks on quantum computers for which no classical efficient ε-approximation scheme exists.