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Neutral-Atom-based Quantum Optimization for Resource Allocation in NOMA Networks
Patatchona Keyela, Remon Polus, Soumaya Cherkaoui, Ola Ahmad
TL;DR
Wireless resource optimization in NOMA networks is difficult, and neutral-atom quantum approaches to mobile-communication optimization remain largely unexplored. The paper reformulates the maximum access problem as a maximum independent set problem and solves it using Pasqal’s neutral-atom emulator. Its emulator curves exactly match the Gurobi solver and both outperform random allocation.
Problem
Neutral-atom quantum approaches to mobile-communication optimization remain largely unexplored, while resource allocation must manage growing users and interactions.
Source: §I · p. 1Method
The paper maps the uplink NOMA maximum access problem to a conflict graph and uses Pasqal’s Pulser emulator to solve the resulting MIS problem.
Source: §I · p. 1, A. Conflict Graph Construction and… · p. 3Results
Pasqal emulator curves exactly match the Gurobi solver’s performance, and both significantly outperform random allocation in supported users.
Source: §V · p. 5Takeaways & Limitations
The numerical evaluations validate the feasibility and effectiveness of the neutral-atom emulator framework for maximizing user access while satisfying system requirements.
Source: §VI · p. 6
Abstract
from arXiv · showhide
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.
I. Introduction
NOMA can support multiple users on shared resources, but growing user populations make resource allocation increasingly difficult. This paper addresses the limited use of neutral-atom quantum computing for wireless optimization by reformulating uplink NOMA resource allocation as a graph problem and evaluating a neutral-atom emulator.
I. Introduction
- NOMA lets multiple users share resources, while conventional allocation and scheduling struggle to manage growing users and interactions.OMA assigns distinct resources to users, limiting simultaneous service; NOMA uses power-domain user diversity and successive interference cancellation.Source: §I · p. 1
- The paper targets the largely unexplored use of neutral-atom quantum computing for mobile-communication optimization.It focuses on the maximum access problem in an uplink NOMA network, jointly considering admission control, power allocation, and channel assignment.Source: §I · p. 1
- The maximum access problem is reformulated as a conflict graph involving admission control, user clustering, power control, and channel assignment.The graph is addressed using Pasqal’s Pulser emulator, designed to solve combinatorial optimization problems through quantum adiabatic evolution.Source: §I · pp. 1–2
- The paper presents numerical results comparing the emulator’s MIS solutions with a classical optimal solver.The introduction identifies this comparison as a validation of the neutral-atom emulator approach.Source: §I · p. 2
II. System Model
The system model is an uplink NOMA network in which a base station serves ground users in clusters over available channels. It assumes ideal synchronization and successive interference cancellation, and limits each channel to two users.
II. System Model
- The base station serves ground users in NOMA clusters over a set of uplink channels, with exactly two users per channel.Users with weaker channel conditions receive higher transmit power than users with stronger channel gain.Source: §II · p. 2
- A binary admission variable indicates whether each user is admitted, and a binary channel assignment variable indicates the channel assigned to that user.The model assumes perfect time and frequency synchronization and an ideal SIC receiver that cancels previously decoded interference without residual error.Source: §II · p. 2
- The model defines each user’s SINR using transmit power, channel power gain, interference, and additive white Gaussian noise.Channel gain incorporates small-scale fading and distance-based path loss; achievable rate is based on Shannon’s theorem and the bandwidth allocated per channel.Source: §II · p. 2
III. Problem Formulation
The formulation maximizes the number of admitted users subject to rate, power, and channel-assignment requirements. Because it is a mixed-integer problem, it is related to maximum independent set through a conflict representation of feasible NOMA cluster–channel pairs.
III. Problem Formulation
- The objective is to maximize admitted users while meeting minimum-rate, transmit-power, and channel-assignment requirements.Each selected user must meet the minimum data rate, remain within transmit power limits, and be assigned to at most one frequency channel.Source: §III · p. 2
- The constraints enforce minimum rate and maximum power, prohibit assigning a user to multiple channels, and require exactly two users per channel.Admission and channel-assignment decisions are binary.Source: §III · pp. 2–3
- The problem combines discrete admission and assignment variables with continuous power variables, making it NP-hard in general.The paper relates its objective to MIS by representing mutually exclusive NOMA cluster–channel pairs as vertices whose conflicts correspond to adjacent vertices.Source: §III · pp. 2–3
A. Conflict Graph Construction and Cluster Feasibility
The conflict graph represents feasible NOMA cluster–channel choices as vertices and admission conflicts as edges, enabling the MAP to be treated as an MIS problem. Candidate clusters must meet each user’s minimum-rate and maximum-power constraints.
A. Conflict Graph Construction and Cluster Feasibility
- Each graph vertex is a feasible NOMA cluster–channel pair, and an edge marks pairs that share a user or channel and cannot be admitted together.A cluster is a pair of users on a channel that satisfies constraints C1 and C2.Source: A. Conflict Graph Construction and… · p. 3
- A candidate cluster is feasible only if every user meets the minimum data-rate and maximum transmit-power constraints.Source: A. Conflict Graph Construction and… · p. 3
- The construction generates candidate vertices before checking vertex pairs for conflicts; edge construction dominates, with worst-case complexity O(|V|^2).Power and rate constraints discard many candidate vertices in practical settings, making the graph sparser and effective cost well below the worst-case bound.Source: A. Conflict Graph Construction and… · p. 3
IV. Neutral-Atom Quantum (NAQ) Optimization
The NAQ framework solves the Section III problem using Rydberg-state interactions and adiabatic evolution. The system evolves from an initial Hamiltonian to a problem-specific Hamiltonian whose ground state encodes the optimal solution.
IV. Neutral-Atom Quantum (NAQ) Optimization
- The NAQ approach is proposed to solve the optimization problem formulated in Section III.Source: §IV · p. 3
- Rydberg blockade provides tunable, distance-dependent interactions between neutral atoms.Source: §IV · p. 3
- Adiabatic evolution takes the platform from an initial Hamiltonian to a problem-specific Hamiltonian whose ground state encodes the optimal solution.Source: §IV · p. 3
A. Rydberg States and the Rydberg Blockade Effect
Rydberg states place an electron at a large distance from the nucleus, enabling strong interactions between atoms. These interactions create a blockade radius within which simultaneous excitation is prevented.
A. Rydberg States and the Rydberg Blockade Effect
- A Rydberg state is an electronic configuration with an electron excited to a high principal quantum number and located far from the nucleus.The electron is weakly bound and forms orbitals significantly larger than those of the ground state.Source: A. Rydberg States and the Rydberg… · p. 3
- Excitation to a Rydberg state induces strong van der Waals interactions that shift neighboring atoms’ energy levels.Source: A. Rydberg States and the Rydberg… · p. 3
- Within the blockade radius Rb, energy shifts make the doubly excited state off-resonant, preventing simultaneous excitation of neighboring atoms.The blockade radius is defined using the van der Waals coefficient C6, Rabi frequency Ω, and reduced Planck constant ℏ.Source: A. Rydberg States and the Rydberg… · p. 4
B. Neutral-Atom-Based Quantum Optimization Approach
The neutral-atom approach uses laser-controlled qubits and Rydberg interactions to represent a unit disk graph, whose MIS corresponds to the system Hamiltonian’s ground state. Repeated measurements yield candidate MIS solutions that map to conflict-free NOMA cluster–channel assignments.
B. Neutral-Atom-Based Quantum Optimization Approach
- Optical tweezers and focused laser pulses trap and manipulate atoms as qubits, while time-varying drive parameters control coherent transitions between ground and Rydberg states.The Hamiltonian’s van der Waals interaction varies with interatomic distance as r^-6 and produces the blockade effect.Source: B. Neutral-Atom-Based Quantum… · p. 4
- Qubit positions form a unit disk graph: vertices within distance Rb cannot both be excited, so the Hamiltonian ground state encodes the graph’s maximum independent set.Source: B. Neutral-Atom-Based Quantum… · p. 4
- Repeated measurements produce bitstrings for candidate MIS solutions; the most frequent correspond to the largest independent sets and identify simultaneously admissible NOMA clusters.Each selected cluster represents two admitted users, and the number of occupied channels equals the number of selected clusters.Source: B. Neutral-Atom-Based Quantum… · p. 4
V. Numerical Results
The Pasqal emulator matches Gurobi and outperforms random allocation in supported users. Supported-user counts fall as path loss or minimum-rate requirements increase, while graph complexity and fading conditions shape the results.
V. Numerical Results
- As η increases, stronger signal attenuation reduces received signal strength and the average number of users meeting the data-rate threshold.The emulator and Gurobi curves match across the evaluated path-loss conditions.Source: §V · pp. 4–5
- Pasqal’s emulator exactly matches Gurobi, and both significantly outperform random allocation in supported users.Fig. 2 compares the average number of supported users across path-loss exponents.Source: Figure 2 · p. 5, §V · p. 5
- At η = 2.5, the conflict graph averages 1,900 vertices and 495,702 edges, with both counts decreasing as η rises.Higher path loss limits links that satisfy quality-of-service constraints.Source: Figure 3 · p. 5, §V · p. 5
- Across the considered σ values, higher minimum data rates reduce supported users, while σ = 5 supports significantly more users than σ = 0.5.The paper attributes the σ difference to average channel gain and achievable rates.Source: §V · pp. 5–6, Figure 4 · p. 6
VI. Conclusion
The paper applies neutral-atom quantum optimization to the uplink NOMA maximum access problem by transforming its mixed-integer formulation into an MIS problem. Numerical evaluations support the framework’s feasibility and effectiveness, and future work targets broader wireless optimization tasks.
VI. Conclusion
- The uplink NOMA maximum access problem jointly involves admission control, user clustering, power allocation, and channel assignment before transformation to MIS.The approach uses Pasqal’s Pulser emulator and Rydberg atom arrays to solve the MIS problem through hardware physical constraints.Source: §VI · p. 6
- Numerical evaluations validate the framework’s feasibility and effectiveness in maximizing user access while satisfying system requirements.Source: §VI · p. 6
- Future work will extend the approach to broader wireless tasks, including joint resource allocation, interference management, and network slicing.Source: §VI · p. 6