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International Conference on Information Networking

High-Speed Resource Allocation for Multi-User NOMA Systems Using a Coherent Ising Machine

Shuho Ishibashi, Maki Arai, Aohan Li, Hiroki Takesue, Kensuke Inaba, Kazuyuki Aihara, Mikio Hasegawa

Published Jan 15, 2025• 0 citations
Publisher

Abstract

Non-Orthogonal Multiple Access (NOMA) is a nextgeneration communication technology that enables multiple users share the same wireless channels. To optimize the performance of NOMA, appropriate channel allocation for each user is essential. Previous research has applied a fast optimization approach using the coherent Ising machine (CIM) to channel allocation in NOMA, multiplexing up to two users per channel, which can be formulated as a basic Ising Hamiltonian including up to second-order interactions. However, NOMA can support multiplexing more than two users per channel depending on channel conditions. This paper propose a method for optimizing NOMA systems with more than two multiplexed users per channel, which becomes a Higher Order Binary Optimization problem. We apply a method to reduce the order of the objective function, converting it to Quadratic Unconstrained Binary Optimization, and derive the Ising Hamiltonian for higher-order NOMA. We evaluate our proposed method through simulations using the CIM for optimization. Our results show that the proposed method leads to better solutions than conventional methods.

DOI
10.1109/icoin63865.2025.10992949

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Non-Orthogonal Multiple Access (NOMA) is a nextgeneration communication technology that enables multiple users share the same wireless channels. To optimize the performance of NOMA, appropriate channel allocation for each user is essential. Previous research has applied a fast optimization approach using the coherent Ising machine (CIM) to channel allocation in NOMA, multiplexing up to two users per channel, which can be formulated as a basic Ising Hamiltonian including up to second-order interactions. However, NOMA can support multiplexing more than two users per channel depending on channel conditions. This paper propose a method for optimizing NOMA systems with more than two multiplexed users per channel, which becomes a Higher Order Binary Optimization problem. We apply a method to reduce the order of the objective function, converting it to Quadratic Unconstrained Binary Optimization, and derive the Ising Hamiltonian for higher-order NOMA. We evaluate our proposed method through simulations using the CIM for optimization. Our results show that the proposed method leads to better solutions than conventional methods.
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Non-orthogonal multiple access (NOMA) has been recognized as one of the key enabling technologies for future generation wireless networks. Sharing the same time-frequency resource among users imposes secrecy challenges in NOMA in the presence of untrusted users. This paper characterizes the impact of user-pair selection on the secrecy performance of an untrusted NOMA system. In this regard, an optimization problem is formulated to maximize the secrecy rate of the strong user while satisfying the quality of service (QoS) demands of the user with poorer channel conditions. To solve this problem, we first obtain optimal power allocation in a two-user NOMA system, and then investigate the user-pair selection problem in a more generalized four user NOMA system. Extensive performance evaluations are conducted to validate the accuracy of the proposed results and present valuable insights on the impact of various system parameters on the secrecy performance of the NOMA communication system.
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Recently, new optimization machines based on non-silicon physical systems, such as quantum annealing machines, have been developed, and their commercialization has been started. These machines solve the problems by searching the state of the Ising spins, which minimizes the Ising Hamiltonian. Such a property of minimization of the Ising Hamiltonian can be applied to various combinatorial optimization problems. In this paper, we introduce the coherent Ising machine (CIM), which can solve the problems in a milli-second order, and has higher performance than the quantum annealing machines especially on the problems with dense mutual connections in the corresponding Ising model. We explain how a target problem can be implemented on the CIM, based on the optimization scheme using the mutually connected neural networks. We apply the CIM to traveling salesman problems as an example benchmark, and show experimental results of the real machine of the CIM. We also apply the CIM to several combinatorial optimization problems in wireless communication systems, such as channel assignment problems. The CIM's ultra-fast optimization may enable a real-time optimization of various communication systems even in a dynamic communication environment.
Non-orthogonal multiple access (NOMA) is a key technology for 5G and beyond, enabling more devices to communicate simultaneously than the traditional orthogonal frequency-division multiple access (OFDMA) of 4G. However, the underlying optimization problem for NOMA resource allocation is NPhard. It is possible to formulate this allocation problem as a quadratic unconstrained binary optimization (QUBO) problem to benefit from specialized solvers, but existing software-based solvers are often too slow for real-time implementationIn this paper, we address this bottleneck by proposing a hybrid constraint handling strategy applicable to a wide class of QUBO problems. We introduce the swap-based simulated annealing (SA) solver to implement this strategy and present its implementation on a field-programmable gate array (FPGA) for significant acceleration. Our experimental results demonstrate that the proposed solver on FPGA achieves a 49.2 times speedup compared to PyQUBO and 5.11 times speedup compared to a C++ implementation of the same algorithm while maintaining comparable solution optimality.
Designing a secure non-orthogonal multiple access (NOMA) system has recently sparked a lot of interest among researchers due to its competency over bandwidth utilization. This paper addresses the critical security issue that arises from the adoption of successive interference cancellation based decoding approach in a two-user untrusted NOMA scenario. With the objective of maximizing secrecy fairness between users, a joint optimization problem of power allocation and decoding order is investigated to maximize the minimum ergodic secrecy rate between users. The optimized solutions are obtained by proposing a low computational complexity iterative method. In addition, closed-form optimal solutions based on a tight approximation are presented. Finally, numerical simulations validate the key nontrivial analytical claims and demonstrate that substantial performance gain is achieved over existing benchmark schemes.