Active RIS-Assisted Uplink NOMA with MADDPG for Remote State Estimation in Wireless Sensor Networks

Non-orthogonal multiple access (NOMA) and reconfigurable intelligent surfaces (RISs) are recognized as key technologies for beyond 5G and 6G wireless communications. To address the high computational complexity and non-convex optimization challenges, this letter proposes an optimization framework ba...

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Bibliographic Details
Published inSensors (Basel, Switzerland) Vol. 25; no. 15; p. 4878
Main Authors Li, Rongzhen, Xu, Lei
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 07.08.2025
MDPI
Subjects
Accuracy
Adaptability
Decision making
Energy efficiency
Internet of Things
MADDPG algorithm
Optimization
Parameter estimation
RIS
RSE error
Sensors
uplink NOMA
wireless sensor networks
wireless sensor networks
RIS
uplink NOMA
RSE error
MADDPG algorithm
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Summary:Non-orthogonal multiple access (NOMA) and reconfigurable intelligent surfaces (RISs) are recognized as key technologies for beyond 5G and 6G wireless communications. To address the high computational complexity and non-convex optimization challenges, this letter proposes an optimization framework based on the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm. The proposed framework jointly makes use of sensor grouping, power allocation, an RIS computation strategy, and phase shifts to minimize the remote state estimation (RSE) error. Simulation results demonstrate that the MADDPG algorithm, when applied in an RIS-assisted NOMA system, significantly reduces the RSE error.
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These authors contributed equally to this work.
ISSN:1424-8220
1424-8220
DOI:10.3390/s25154878