User pairing using laser chaos decision maker for NOMA systems

Duan, Zengchao; Li, Aohan; Okada, Norihiro; Yusuke, Ito; Chauvet, Nicolas; Naruse, Makoto; Hasegawa, Mikio

doi:10.1587/nolta.13.72

Cited by 9 publications

(16 citation statements)

References 20 publications

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“…e proposed scheme to select the best laser chaos with the best autocorrelation can accelerate performance in applications such as wireless communication systems [11][12][13].…”

Section: Discussionmentioning

confidence: 99%

“…i -1 e meaning of equation ( 16) is similar to equation ( 14). Q(N − 1) in the right-hand side of equation ( 16) has been already defined in equation (13). As in Case 2, the threshold level can be maintained at the edge, which is shown by Q(N) in equation (16).…”

Section: Threshold Levelmentioning

confidence: 95%

“…Furthermore, the applications of laser chaos decisionmakers have been studied to benefit from their prompt adaptation abilities in dynamically changing uncertain environments [11][12][13][14]. Takeuchi et al applied laser chaos decision-making to channel selection problems in wireless communications [11], in which communication channels suffer from dynamically changing disturbances due to traffic, interference, or fading [15].…”

Section: Introductionmentioning

confidence: 99%

“…Kanemasa et al extended the principle using laser chaos decision-maker to channel bonding in IEEE 802.11ac networks [12]. Furthermore, Duan et al optimized user-pairing in non-orthogonal multiple access (NOMA) systems by laser chaos decisionmaker [13]. Moreover, Kanno et al combined laser chaosbased decision-making with photonic reservoir computing, where adaptive model selection is realized to enhance the computing capability [14].…”

Section: Introductionmentioning

confidence: 99%

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Theory of Acceleration of Decision‐Making by Correlated Time Sequences

et al. 2022

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Photonic accelerators have been intensively studied to provide enhanced information processing capability to benefit from the unique attributes of physical processes. Recently, it has been reported that chaotically oscillating ultrafast time series from a laser, called laser chaos, provides the ability to solve multi-armed bandit (MAB) problems or decision-making problems at GHz order. Furthermore, it has been confirmed that the negatively correlated time-domain structure of laser chaos contributes to the acceleration of decision-making. However, the underlying mechanism of why decision-making is accelerated by correlated time series is unknown. In this study, we demonstrate a theoretical model to account for accelerating decision-making by correlated time sequence. We first confirm the effectiveness of the negative autocorrelation inherent in time series for solving two-armed bandit problems using Fourier transform surrogate methods. We propose a theoretical model that concerns the correlated time series subjected to the decision-making system and the internal status of the system therein in a unified manner, inspired by correlated random walks. We demonstrate that the performance derived analytically by the theory agrees well with the numerical simulations, which confirms the validity of the proposed model and leads to optimal system design. This study paves the way for improving the effectiveness of correlated time series for decision-making, impacting artificial intelligence and other applications.

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“…e proposed scheme to select the best laser chaos with the best autocorrelation can accelerate performance in applications such as wireless communication systems [11][12][13].…”

Section: Discussionmentioning

confidence: 99%

Section: Threshold Levelmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Theory of Acceleration of Decision‐Making by Correlated Time Sequences

et al. 2022

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“…In fact, the solutions to large-scale multi-armed bandit problems are expected to exploit the unique advantages of light, such as temporal, spatial, and wavelength domain multiplexing. These solutions are useful in communication applications, such as channel selection 24 , 25 and non-orthogonal multiple access (NOMA) 26 .…”

Section: Introductionmentioning

confidence: 99%

Decision making for large-scale multi-armed bandit problems using bias control of chaotic temporal waveforms in semiconductor lasers

Morijiri

Mihana

Kanno

et al. 2022

Sci Rep

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Decision making using photonic technologies has been intensively researched for solving the multi-armed bandit problem, which is fundamental to reinforcement learning. However, these technologies are yet to be extended to large-scale multi-armed bandit problems. In this study, we conduct a numerical investigation of decision making to solve large-scale multi-armed bandit problems by controlling the biases of chaotic temporal waveforms generated in semiconductor lasers with optical feedback. We generate chaotic temporal waveforms using the semiconductor lasers, and each waveform is assigned to a slot machine (or choice) in the multi-armed bandit problem. The biases in the amplitudes of the chaotic waveforms are adjusted based on rewards using the tug-of-war method. Subsequently, the slot machine that yields the maximum-amplitude chaotic temporal waveform with bias is selected. The scaling properties of the correct decision-making process are examined by increasing the number of slot machines to 1024, and the scaling exponent of the power-law distribution is 0.97. We demonstrate that the proposed method outperforms existing software algorithms in terms of the scaling exponent. This result paves the way for photonic decision making in large-scale multi-armed bandit problems using photonic accelerators.

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Ultrafast Resource Allocation by Parallel Bandit Architecture Using Chaotic Lasers for Downlink NOMA Systems

Sugiyama,

Mihana,

et al. 2024

IEEE Access

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The effectiveness of laser chaos decision-makers in facilitating ultrafast decision-making makes it possible for a real-time process of channel allocation scheme for the non-orthogonal multiple access (NOMA) technology in the next generation of wireless communications. However, managing the increasing number of users is challenging as the complexity of channel allocation increases significantly. To resolve this challenge, this paper proposes a novel approach to address scalability problems by introducing a parallel bandit architecture using an array of laser chaos decision-makers. In the proposed method, each user is allocated a specific channel by a dedicated laser chaos decision-maker, thereby reducing the number of available options compared with the conventional approach. This parallel bandit architecture enables the system to efficiently manage increasing users while maintaining scalability and ultrafast channel allocation in NOMA. Additionally, fairness is considered by incorporating a logarithmic utility function for design compensation. Numerical simulation results demonstrate that the proposed method achieves higher throughput and enhanced fairness than conventional NOMA approaches such as minimum distance-NOMA (MD-NOMA), conventional-NOMA (C-NOMA), and uniformed channel gain difference-NOMA (UCGD-NOMA). Moreover, the system performance is evaluated on a larger scale, accommodating a significant number of users, with the study considering up to 64 users, surpassing the limitations of the conventional approach of one laser chaos decision-maker, which is constrained to 10 users. INDEX TERMSNon-orthogonal multiple access (NOMA), channel allocation, logarithmic utility function, laser chaos decision-maker, multi-armed bandit problem I. INTRODUCTION VOLUME XX, XXXX

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User pairing using laser chaos decision maker for NOMA systems

Cited by 9 publications

References 20 publications

Theory of Acceleration of Decision‐Making by Correlated Time Sequences

Theory of Acceleration of Decision‐Making by Correlated Time Sequences

Decision making for large-scale multi-armed bandit problems using bias control of chaotic temporal waveforms in semiconductor lasers

Ultrafast Resource Allocation by Parallel Bandit Architecture Using Chaotic Lasers for Downlink NOMA Systems

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