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arXiv:2407.21547 · IEEE International Conference on Quantum Computing and Engineering (QCE)

Scheduling Quantum Annealing for Active User Detection in a NOMA Network

Romain Piron, Claire Goursaud

Published Sep 15, 2024• 3 citations
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Abstract

Active user detection in a non-orthogonal multiple access (NOMA) network is a major challenge for 5G/6G applications. However, classical algorithms that can perform this task suffer either from complexity or reduced performances. This work aims at proposing a quantum annealing approach to overcome this trade-off. Firstly, we show that the maximum a posteriori decoder of the activity pattern of the network can be seen as the ground state of an Ising Hamiltonian. For N users in a network with perfect channels, we propose a universal control function to schedule the annealing process. Our approach avoids to continuously compute the optimal control function but still ensures high success probability while demanding a lower annealing time than a linear control function. This advantage holds even in the presence of imperfections in the network.

DOI
10.1109/qce60285.2024.00057

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Active user detection in a non-orthogonal multiple access (NOMA) network is a major challenge for 5G/6G applications. However, classical algorithms that can perform this task suffer either from complexity or reduced performances. This work aims at proposing a quantum annealing approach to overcome this trade-off. Firstly, we show that the maximum a posteriori decoder of the activity pattern of the network can be seen as the ground state of an Ising Hamiltonian. For N users in a network with perfect channels, we propose a universal control function to schedule the annealing process. Our approach avoids to continuously compute the optimal control function but still ensures high success probability while demanding a lower annealing time than a linear control function. This advantage holds even in the presence of imperfections in the network.
Detecting active users in a non-orthogonal multiple access (NOMA) network poses a significant challenge for 5G/6G applications. Traditional algorithms tackling this task, relying on classical processors, have to make a compromise between performance and complexity. However, a quantum computing based strategy called quantum annealing (QA) can mitigate this tradeoff. In this paper, we first propose a mapping between the AUD searching problem and the identification of the ground state of an Ising Hamiltonian. Then, we compare the execution times of our QA approach for several code domain multiple access (CDMA) scenarios. We evaluate the impact of the cross-correlation properties of the chosen codes in a NOMA network for detecting the active user's set.
Quantum Annealing (QA) uses quantum fluctuations to search for a global minimum of an optimization-type problem faster than classical computer. To meet the demand for future internet traffic and mitigate the spectrum scarcity, this work presents the QA-aided maximum likelihood (ML) decoder for multi-user non-orthogonal multiple access (NOMA) networks as an alternative to the successive interference cancellation (SIC) method. The practical system parameters such as channel randomness and possible transmit power levels are taken into account for all individual signals of all involved users. The brute force (BF) and SIC signal detection methods are taken as benchmarks in the analysis. The QA-assisted ML decoder results in the same BER performance as the BF method outperforming the SIC technique, but the execution of QA takes more time than BF and SIC. The parallelization technique can be a potential aid to fasten the execution process. This will pave the way to fully realize the potential of QA decoders in NOMA systems.
A new method to realize computation of the log-likelihood ratio (LLR) in multi-user detection (MUD) by quantum annealing (QA) is proposed herein. One metaheuristic algorithm for solving combinatorial optimization problems is QA. Recently, QA has been applied in various fields to hasten computations. This study specifically examines the application of QA in up-link non-orthogonal multiple access (UL-NOMA) that employs iterative MUD. Our proposed method, QA-aided MUD, uses QA to calculate LLR in iterative MUD. We tested QA-aided MUD with a D-Wave quantum annealer. The error rate analysis demonstrates that QA-aided MUD has comparable performance to that of conventional MUD method. Furthermore, when the annealing time was set to 20 µs, we demonstrated than that the total computation time is 1/10 of the computation time necessary when using a digital computer. We also evaluated the convergence behavior of QA-aided MUD through evolution of mutual information. The results indicate that QA-assisted MUD has almost identical convergence performance to that of the conventional MUD method for LLR calculations.
The strong growth in the number of connected mobile devices has imposed new challenges in efficiently exploiting the available networks resources. Code Domain Non-Orthogonal Multiple Access (NOMA) technique appears as a tremendous efficient solution. Each device uses its assigned code to simultaneously transmit its data along with the user identifier, without any resource reservation exchange, saving precious wireless resources. However, this requires a receiver capable of blindly detecting the active users, which is highly complex. Driven by the promising superposition property of quantum architecture, the goal of this paper is to adapt and apply the quantum Grover algorithm for Active User Detection (AUD) purpose in the context of NOMA, to alleviate the search complexity. This adapted Grover’s algorithm is compared with the optimal classical Maximum Likelihood (ML) AUD receivers, as well as with the basic classical Conventional Correlation Receiver (CCR). A benchmark on the probability of AUD is assessed as a function of the Signal to Noise Ratio (SNR) of the received signal. We show that our adapted Grover’s algorithm is very promising in high SNR regime.
As wireless networks advance toward the Sixth Generation (6G), which will support highly heterogeneous scenarios and massive data traffic, conventional computing methods may struggle to meet the immense processing demands in a resource-efficient manner. This paper explores the potential of quantum computing (QC) to address these challenges, specifically by enhancing the efficiency of Maximum-Likelihood detection in Multiple-Input Multiple-Output (MIMO) Non-Orthogonal Multiple Access (NOMA) communication systems, an essential technology anticipated for 6G. The study proposes the use of the Quantum Approximate Optimization Algorithm (QAOA), a variational quantum algorithm known for providing quantum advantages in certain combinatorial optimization problems. While current quantum systems are not yet capable of managing millions of physical qubits or performing high-fidelity, long gate sequences, the results indicate that QAOA is a promising QC approach for radio signal processing tasks. This research provides valuable insights into the potential transformative impact of QC on future wireless networks. This sets the stage for discussions on practical implementation challenges, such as constrained problem sizes and sensitivity to noise, and opens pathways for future research aimed at fully harnessing the potential of QC for 6G and beyond.
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.