Energy Efficiency Maximization in RIS-Assisted SWIPT Networks With RSMA: A PPO-Based Approach

Zhang, Ruichen; Xiong, Ke; Lu, Yang; Fan, Pingyi; Ng, Derrick Wing Kwan; Letaief, Khaled B.

doi:10.1109/jsac.2023.3240707

Cited by 57 publications

(13 citation statements)

References 58 publications

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“…In our problem (21), the action space comprises both continuous and discrete variables, culminating in a hybrid action space [48]. To navigate this complexity, one could manipulate the continuous action space to select discrete actions [48], [49], e.g., by generating a 10-dimensional action vector with values ranging between 0 and 1, and subsequently choosing the action corresponding to the position of the maximum value. This methodology is plausible due to the continuous relaxation of discrete action spaces, allowing gradient-based optimization methods, like DDPG, to operate.…”

Section: Gdm-based Ddpg With Llms Interaction For Joint Resource Allo...mentioning

confidence: 99%

Exploring Collaborative Distributed Diffusion-Based AI-Generated Content (AIGC) in Wireless Networks

Du¹,

Ruichen²,

Niyato³

et al. 2024

IEEE Network

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Distributed Artificial Intelligence-Generated Content (AIGC) has attracted increasing attention. However, it faces two significant challenges: how to maximize the subjective Quality of Experience (QoE) and how to enhance the energy efficiency, which are particularly pronounced in widely adopted Generative Diffusion Model (GDM)-based AIGC services for image generation. In this paper, we propose a novel user-centric Interactive AI (IAI) approach for service management, with a distributed GDM-based AIGC framework, prioritizing efficient and collaborative GDM deployment. Specifically, we restructure the GDM's inference process, i.e., the denoising chain, to enable users' semantically similar prompts to share a portion of diffusion steps. Furthermore, to maximize the users' subjective QoE, we propose a IAI approach, i.e., Reinforcement Learning With Large Language Models Interaction (RLLI), which utilizes Large Language Model (LLM)-empowered generative agents to replicate users interaction, providing real-time and subjective QoE feedback that reflects a spectrum of user personalities. Lastly, we present the GDM-based Deep Deterministic Policy Gradient (G-DDPG) algorithm, adapted to the proposed RLLI framework, for effective communication and computing resource allocation while considering user subjective personalities and dynamic wireless environments in decision-making. Simulation results show that G-DDPG can increase the sum QoE by 15%, compared with the conventional DDPG algorithm.

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Section: Gdm-based Ddpg With Llms Interaction For Joint Resource Allo...mentioning

confidence: 99%

Exploring Collaborative Distributed Diffusion-Based AI-Generated Content (AIGC) in Wireless Networks

Du¹,

Ruichen²,

Niyato³

et al. 2024

IEEE Network

View full text Add to dashboard Cite

show abstract

“…Meanwhile, for any given C S U l , the outer optimization problem (19) is solved by the SDR technique. Moreover, constraint (18d) and (18e) can be equivalently expressed by (20) and (21), respectively.…”

Section: Problem Formulationmentioning

confidence: 99%

“…The system considered two sets of users: one set dedicated to decoding information and another set focused solely on harvesting energy, with the latter group being deemed potential eavesdroppers. The authors in [20] considered RSMA in a MISO SWIPT system assisted by an intelligent reflecting surface. Their aim was to maximize energy efficiency subject to rate, energy, and power constraints.…”

Section: Introductionmentioning

confidence: 99%

Rate-Splitting Multiple Access for Secure Communications Over CR MISO SWIPT Systems With Non-Linear EH Users

Garcia,

Camana,

Querol

et al. 2024

IEEE Trans. on Green Commun. Netw.

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In this paper, we investigate a secure transmission for a rate-splitting multiple-access (RSMA)-based multiple-input single-output (MISO) underlay cognitive radio (CR) system. The proposed network is composed of a set of secondary users (SUs) that utilize simultaneous wireless information and power transfer (SWIPT) technology and an additional set of non-linear energy harvesting (EH) users. Moreover, the system model under consideration is exposed to multiple eavesdroppers. Thus, we propose to minimize the transmit power intended to the SUs and EH users while maximizing the artificial noise (AN) generated by the secondary transmitter, aiming to counter eavesdroppers' wiretaps while satisfying the quality-of-service constraints. Therefore, we develop a novel approach based on ant colony regression (ACOR) and semidefinite relaxation (SDR) methods to solve the challenging and non-convex problem which is further transformed into a bilevel optimization problem. Afterward, we investigate a comparative solution based on the particle swarm optimization (PSO) algorithm, the successive convex approximation (SCA) technique, and analyze the incidence of linear and non-linear EH designs. In addition, we compare the RSMA-based scheme with non-orthogonal multiple-access (NOMA), space-division multiple access (SDMA), and zeroforcing (ZF) techniques. Satisfactorily, simulation results prove the proposed ACOR-SDR framework achieves better performance and lower complexity than its counterparts.

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“…Regarding the limited battery challenge although several energy harvesting methods, such as solar and wind energy harvesting, can capture energy from environment, their availability is out of control [4]. To prolong the operational lifetime of the energy-constrained and low-power devices, simultaneous wireless information and power transfer (SWIPT) has been proposed, which offers a controllable way to charge devices by utilizing the ubiquitous radio-frequency (RF) signals [5]. SWIPT enables devices to receive power and information simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Design and Performance Analysis of RIS-Aided DCSK-WPC System With Energy Buffer

Xie

Cai

Kaddoum³

2023

IEEE Trans. Commun.

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In this paper, we propose a simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) and energy buffer aided multiple-input single-output (MISO) simultaneous wireless information and power transfer (SWIPT) nonorthogonal multiple access (NOMA) system, which consists of a STAR-RIS, an access point (AP), and reflection users and transmission users with energy buffers. In the proposed system, the multi-antenna AP can transmit information and energy to several single-antenna reflection and transmission users simultaneously in a NOMA fashion, where the power transfer and information transmission states of the users are modeled using Markov chains. The reflection and transmission users harvest and store the energy in energy buffers as additional power supplies. The power outage probability, information outage probability, sum throughput, and joint outage probability closed-form expressions of the proposed system are derived over Nakagami-m fading channels, which are validated via simulations. Results demonstrate that the proposed system achieves better performance in comparison to the STAR-RIS aided MISO SWIPT-NOMA buffer-less, conventional RIS and energy buffer aided MISO SWIPT-NOMA, and STAR-RIS and energy buffer aided MISO SWIPT-time-division multiple access (TDMA) systems. Furthermore, a particle swarm optimization based power allocation (PSO-PA) algorithm is designed to maximize the sum throughput with a constraint on the joint outage probability. Simulation results illustrate that the proposed PSO-PA algorithm can achieve an improved sum throughput performance of the proposed system. Index Terms-Simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS), energy buffer, simultaneous wireless information and power transfer (SWIPT), non-orthogonal multiple access (NOMA), Markov chains.

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Energy Efficiency Maximization in RIS-Assisted SWIPT Networks With RSMA: A PPO-Based Approach

Cited by 57 publications

References 58 publications

Exploring Collaborative Distributed Diffusion-Based AI-Generated Content (AIGC) in Wireless Networks

Exploring Collaborative Distributed Diffusion-Based AI-Generated Content (AIGC) in Wireless Networks

Rate-Splitting Multiple Access for Secure Communications Over CR MISO SWIPT Systems With Non-Linear EH Users

Design and Performance Analysis of RIS-Aided DCSK-WPC System With Energy Buffer

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