CORTEXA
← Browse
crossrefElectronics2025-01-31Cited by 2

Channel Prediction Technology Based on Adaptive Reinforced Reservoir Learning Network for Orthogonal Frequency Division Multiplexing Wireless Communication Systems

Yongbo Sui, Lingshuang Wu, Hui Gao

Channel prediction is an effective technology to support adaptive transmission in wireless communication. To solve the difficulty of accurately predicting channel state information (CSI) due to fast time-varying characteristics, a next-generation reservoir calculation network (NGRCN) is combined with CSI, and a channel prediction method for OFDM wireless communication systems based on an adaptive reinforced reservoir learning network (adaptive RRLN) is proposed. An adaptive elastic network (adaptive EN) is used to estimate the output weight matrix to avoid ill-conditioned solutions. Therefore, the adaptive RRLN has echo and oracle properties. In addition, an adaptive singular spectral analysis (adaptive SSA) method is proposed to improve the local predictability of CSI by decomposing and reconstructing CSI to improve the fitting accuracy of the channel prediction model. In the simulation section, the OFDM wireless communication systems are constructed using IEEE802.11ah and the one-step prediction, the multi-step prediction, and the robustness test are implemented and analyzed. The simulation results show that the prediction accuracy of the adaptive RRLN can reach 3 × 10−5 and 8.36 × 10−6, which offers satisfactory prediction performance and robustness.

View free PDFSource page

Related papers

crossrefElectronics2024-06-21Cited by 77

Autonomous UAV Navigation with Adaptive Control Based on Deep Reinforcement Learning

Yongfeng Yin, Zhetao Wang, Lili Zheng, Qingran Su, Yang Guo

Unmanned aerial vehicle (UAV) navigation plays a crucial role in its ability to perform autonomous missions in complex environments. Most of the existing reinforcement learning methods to solve the UAV navigation problem fix the flight altitude and velocity, which largely reduces…

View free PDFSource page
crossrefElectronics2024-04-09Cited by 4

Novel AMI in Zigbee Satellite Network Based on Heterogeneous Wireless Sensor Network for Global Machine-to-Machine Connectivity

Chia-Lun Wu, Tsung-Tao Lu, Chin-Tan Lee, Jwo-Shiun Sun, Hsin-Piao Lin, Yuh-Shyan Hwang, et al.

This study endeavored to enhance the efficiency and utility of microcomputer meters. In the past, their role was predominantly confined to remote meter reading, entailing high construction and communication transmission costs, coupled with subsequent maintenance and operational e…

View free PDFSource page
openalexElectronics2026-07-24

A Physics-Informed Neural Network for Graph-Based Network Traffic Prediction

Yuhao Zhang, Yuhao Feng, S L Zhang, Peifeng Liang, Wei Guan

Accurate network traffic prediction is important for the autonomy, resilience and resource orchestration of 6G and AI-native communication infrastructures, while also supporting green networking and digital twin network applications. However, existing data-driven prediction model…

View free PDFSource page
crossrefElectronics2025-07-07Cited by 2

Research on Autonomous Vehicle Lane-Keeping and Navigation System Based on Deep Reinforcement Learning: From Simulation to Real-World Application

Chia-Hsin Cheng, Hsiang-Hao Lin, Yu-Yong Luo

In recent years, with the rapid development of science and technology and the substantial improvement of computing power, various deep learning research topics have been promoted. However, existing autonomous driving technologies still face significant challenges in achieving rob…

View free PDFSource page
crossrefElectronics2026-03-26

Implementation of a Wrist-Worn Wireless Sensor System with Machine Learning-Based Classification for Indoor Human Tracking

Thradon Wattananavin, Apidet Booranawong

This work presents the development of a wrist-worn wireless sensor system for high-accuracy indoor human zone tracking. The proposed system employs machine learning techniques to combine data from multiple sources, including a Received Signal Strength Indicator (RSSI) from wirele…

View free PDFSource page
crossrefElectronics2023-10-30Cited by 8

Radio Map-Based Trajectory Design for UAV-Assisted Wireless Energy Transmission Communication Network by Deep Reinforcement Learning

Changhe Chen, Fahui Wu

In this paper, we consider a wireless energy-carrying communication network of a UAV. In this communication network, the internet of things (IoT) devices maintain their work via the power supply of batteries. The energy of batteries is slowly consumed over time. The UAV adopts th…

View free PDFSource page