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Found 89 papers, 9 papers with code
Temporal Convolutional Memory Networks for Remaining Useful Life Estimation of Industrial Machinery
This paper, introduces a system model that incorporates temporal convolutions with both long term and short term time dependencies.
Reconfigurable Intelligent Surface Assisted Multiuser MISO Systems Exploiting Deep Reinforcement Learning
In this paper, we investigate the joint design of transmit beamforming matrix at the base station and the phase shift matrix at the RIS, by leveraging recent advances in deep reinforcement learning (DRL).
RF-Based Direction Finding of UAVs Using DNN
This paper presents a sparse denoising autoencoder (SDAE)-based deep neural network (DNN) for the direction finding (DF) of small unmanned aerial vehicles (UAVs).
Few-Shot Specific Emitter Identification via Deep Metric Ensemble Learning
Thus, we focus on few-shot SEI (FS-SEI) for aircraft identification via automatic dependent surveillance-broadcast (ADS-B) signals, and a novel FS-SEI method is proposed, based on deep metric ensemble learning (DMEL).
A Multi-Head Ensemble Multi-Task Learning Approach for Dynamical Computation Offloading
To improve the MEC performance, it is required to design an optimal offloading strategy that includes offloading decision (i. e., whether offloading or not) and computational resource allocation of MEC.
Pervasive Machine Learning for Smart Radio Environments Enabled by Reconfigurable Intelligent Surfaces
The emerging technology of Reconfigurable Intelligent Surfaces (RISs) is provisioned as an enabler of smart wireless environments, offering a highly scalable, low-cost, hardware-efficient, and almost energy-neutral solution for dynamic control of the propagation of electromagnetic signals over the wireless medium, ultimately providing increased environmental intelligence for diverse operation objectives.
A Transferable Multi-stage Model with Cycling Discrepancy Learning for Lithium-ion Battery State of Health Estimation
A transferable multi-stage SOH estimation model is proposed to perform TL across batteries in the same stage, consisting of four steps.
SafeSpace MFNet: Precise and Efficient MultiFeature Drone Detection Network
For optimal bird detection, MFNet-M (Ablation study 2) achieves an impressive precision of 99. 8\%, while for UAV detection, MFNet-L (Ablation study 2) achieves a precision score of 97. 2\%.
Performance Bounds for Near-Field Localization with Widely-Spaced Multi-Subarray mmWave/THz MIMO
By employing the Riemann sum, closed-form CRB expressions are derived for the spherical wavefront-based WSMS (SW-WSMS).
Indoor Sound Source Localization with Probabilistic Neural Network
It is known that adverse environments such as high reverberation and low signal-to-noise ratio (SNR) pose a great challenge to indoor sound source localization.
DCASE 2018 Challenge: Solution for Task 5
To address Task 5 in the Detection and Classification of Acoustic Scenes and Events (DCASE) 2018 challenge, in this paper, we propose an ensemble learning system.
Deep Learning for UL/DL Channel Calibration in Generic Massive MIMO Systems
We then leverage the trained deep neural network with the instantaneously estimated UL channel to calibrate the DL one, which is not observable during the UL transmission phase.
Indoor Signal Focusing with Deep Learning Designed Reconfigurable Intelligent Surfaces
Reconfigurable Intelligent Surfaces (RISs) comprised of tunable unit elements have been recently considered in indoor communication environments for focusing signal reflections to intended user locations.
Benchmarking air-conditioning energy performance of residential rooms based on regression and clustering techniques
In this paper, we propose a data-driven approach to fairly benchmark the AC energy performance of residential rooms.
PSDNet and DPDNet: Efficient channel expansion, Depthwise-Pointwise-Depthwise Inverted Bottleneck Block
To design more efficient lightweight concolutional neural netwok, Depthwise-Pointwise-Depthwise inverted bottleneck block (DPD block) is proposed and DPDNet is designed by stacking DPD block.
Doppler Invariant Demodulation for Shallow Water Acoustic Communications Using Deep Belief Networks
The proposed method comprises of a ML based feature extraction method and classification technique.
Resource Allocation in Mobility-Aware Federated Learning Networks: A Deep Reinforcement Learning Approach
However, federated learning faces the energy constraints of the workers and the high network resource cost due to the fact that a number of global model transmissions may be required to achieve the target accuracy.
Holographic MIMO Surfaces for 6G Wireless Networks: Opportunities, Challenges, and Trends
Future wireless networks are expected to evolve towards an intelligent and software reconfigurable paradigm enabling ubiquitous communications between humans and mobile devices.
Understanding Crowd Behaviors in a Social Event by Passive WiFi Sensing and Data Mining
In this paper, therefore, we propose a comprehensive data analysis framework to fully analyze the collected probe requests to extract three types of patterns related to crowd behaviors in a large social event, with the help of statistics, visualization, and unsupervised machine learning.
Cluster Pruning: An Efficient Filter Pruning Method for Edge AI Vision Applications
Even though the Convolutional Neural Networks (CNN) has shown superior results in the field of computer vision, it is still a challenging task to implement computer vision algorithms in real-time at the edge, especially using a low-cost IoT device due to high memory consumption and computation complexities in a CNN.
Columnwise Element Selection for Computationally Efficient Nonnegative Coupled Matrix Tensor Factorization
Coupled Matrix Tensor Factorization (CMTF) facilitates the integration and analysis of multiple data sources and helps discover meaningful information.
Efficient Nonnegative Tensor Factorization via Saturating Coordinate Descent
With the advancements in computing technology and web-based applications, data is increasingly generated in multi-dimensional form.
Lessons Learned from Accident of Autonomous Vehicle Testing: An Edge Learning-aided Offloading Framework
This letter proposes an edge learning-based offloading framework for autonomous driving, where the deep learning tasks can be offloaded to the edge server to improve the inference accuracy while meeting the latency constraint.
Predictive Maintenance for Edge-Based Sensor Networks: A Deep Reinforcement Learning Approach
In this paper, a model-free Deep Reinforcement Learning algorithm is proposed for predictive equipment maintenance from an equipment-based sensor network context.
Channel Estimation for RIS-Empowered Multi-User MISO Wireless Communications
We also discuss the downlink achievable sum rate computation with estimated channels and different precoding schemes for the base station.
Deep Learning Based Defect Detection for Solder Joints on Industrial X-Ray Circuit Board Images
With some advanced algorithms, the new technologies are expected to control the production quality based on the digital images.
Invariant learning based multi-stage identification for Lithium-ion battery performance degradation
By informing accurate performance (e. g., capacity), health state management plays a significant role in safeguarding battery and its powered system.
Offloading Optimization in Edge Computing for Deep Learning Enabled Target Tracking by Internet-of-UAVs
This motivates us to consider offloading this type of deep learning (DL) tasks to a mobile edge computing (MEC) server due to limited computational resource and energy budget of the UAV, and further improve the inference accuracy.
Hybrid Beamforming for RIS-Empowered Multi-hop Terahertz Communications: A DRL-based Method
Wireless communication in the TeraHertz band (0. 1--10 THz) is envisioned as one of the key enabling technologies for the future six generation (6G) wireless communication systems.
Transforming Energy Networks via Peer to Peer Energy Trading: Potential of Game Theoretic Approaches
Peer-to-peer (P2P) energy trading has emerged as a next-generation energy management mechanism for the smart grid that enables each prosumer of the network to participate in energy trading with one another and the grid.
Secure Beamforming for Multiple Intelligent Reflecting Surfaces Aided mmWave Systems
In this system, the secrecy rate is maximized by controlling the on-off status of each IRS as well as optimizing the phase shift matrix of the IRSs.
Dense Small Satellite Networks for Modern Terrestrial Communication Systems: Benefits, Infrastructure, and Technologies
Dense small satellite networks (DSSN) in low earth orbits (LEO) can benefit several mobile terrestrial communication systems (MTCS).
Urban Space Insights Extraction using Acoustic Histogram Information
In this paper, we study the implementation of low-cost analogue sound sensors to detect outdoor activities and estimate the raining period in an urban residential area.
Multiple-Perspective Clustering of Passive Wi-Fi Sensing Trajectory Data
Information about the spatiotemporal flow of humans within an urban context has a wide plethora of applications.
Refined Nonlinear Rectenna Modeling and Optimal Waveform Design for Multi-User Multi-Antenna Wireless Power Transfer
Leveraging this new rectenna model, we first consider the single-ER case and study the multisine-based power waveform design based on the wireless channel to maximize the harvested power at the ER.
Information Theory Information Theory
A Transfer Learning-based State of Charge Estimation for Lithium-Ion Battery at Varying Ambient Temperatures
After that, once the inability of the reference SoC estimation model is detected, consistent temporal dynamics between temperatures are selected for transfer learning.
Time-Series Regeneration with Convolutional Recurrent Generative Adversarial Network for Remaining Useful Life Estimation
Out of this consideration, an enhanced RUL framework focusing on data self-generation is put forward for both non-cyclic and cyclic degradation patterns for the first time.
Multi-hop RIS-Empowered Terahertz Communications: A DRL-based Hybrid Beamforming Design
We investigate the joint design of digital beamforming matrix at the BS and analog beamforming matrices at the RISs, by leveraging the recent advances in deep reinforcement learning (DRL) to combat the propagation loss.
Underwater Acoustic Communication Receiver Using Deep Belief Network
Our proposed receiver system comprises of DBN based de-noising and classification of the received signal.
Intelligent Spectrum Learning for Wireless Networks with Reconfigurable Intelligent Surfaces
Reconfigurable intelligent surface (RIS) has become a promising technology for enhancing the reliability of wireless communications, which is capable of reflecting the desired signals through appropriate phase shifts.
A Joint Energy and Latency Framework for Transfer Learning over 5G Industrial Edge Networks
In this paper, we propose a transfer learning (TL)-enabled edge-CNN framework for 5G industrial edge networks with privacy-preserving characteristic.
IIoT-Enabled Health Monitoring for Integrated Heat Pump System Using Mixture Slow Feature Analysis
This revolution delivers a promising solution for the health monitoring problem of heat pump (HP) system, a vital device widely deployed in modern buildings for heating use, to timely evaluate its operation status to avoid unexpected downtime.
WiFi Fingerprint Clustering for Urban Mobility Analysis
We propose a system architecture to scan the surrounding WiFi AP, and perform unsupervised learning to demonstrate that it is possible to identify three major insights, namely the indoor POI within a building, neighbourhood activity, and micro-mobility of the users.
Transferable Deep Reinforcement Learning Framework for Autonomous Vehicles with Joint Radar-Data Communications
Autonomous Vehicles (AVs) are required to operate safely and efficiently in dynamic environments.
Relative Localization of Mobile Robots with Multiple Ultra-WideBand Ranging Measurements
We propose an approach to estimate the relative pose between a group of robots by equipping each robot with multiple UWB ranging nodes.
Spectrum Learning-Aided Reconfigurable Intelligent Surfaces for 'Green' 6G Networks
In the sixth-generation (6G) era, emerging large-scale computing based applications (for example processing enormous amounts of images in real-time in autonomous driving) tend to lead to excessive energy consumption for the end users, whose devices are usually energy-constrained.
Lithium-ion Battery State of Health Estimation based on Cycle Synchronization using Dynamic Time Warping
The state of health (SOH) estimation plays an essential role in battery-powered applications to avoid unexpected breakdowns due to battery capacity fading.
Time-Varying Channel Prediction for RIS-Assisted MU-MISO Networks via Deep Learning
To mitigate the effects of shadow fading and obstacle blocking, reconfigurable intelligent surface (RIS) has become a promising technology to improve the signal transmission quality of wireless communications by controlling the reconfigurable passive elements with less hardware cost and lower power consumption.
Slow-varying Dynamics Assisted Temporal Capsule Network for Machinery Remaining Useful Life Estimation
Similarly, the estimation accuracy of the milling machine has been improved by 23. 57% compared to LSTM and 19. 54% compared to CapsNet.
Deep Reinforcement Learning Based on Location-Aware Imitation Environment for RIS-Aided mmWave MIMO Systems
Reconfigurable intelligent surface (RIS) has recently gained popularity as a promising solution for improving the signal transmission quality of wireless communications with less hardware cost and energy consumption.
Multi-Agent Deep Reinforcement Learning for Cost- and Delay-Sensitive Virtual Network Function Placement and Routing
Then, the joint VNF P&R problem is decoupled into two iterative subtasks: placement subtask and routing subtask.
Reconfigurable Intelligent Computational Surfaces: When Wave Propagation Control Meets Computing
The envisioned sixth-generation (6G) of wireless networks will involve an intelligent integration of communications and computing, thereby meeting the urgent demands of diverse applications.
Transfer Learning-based State of Health Estimation for Lithium-ion Battery with Cycle Synchronization
Second, the canonical variates retrieved from the spatial path of the cycle-synchronized time series are used for distribution similarity analysis between the source and target batteries.
Vulnerability of Distributed Inverter VAR Control in PV Distributed Energy System
This work studies the potential vulnerability of distributed control schemes in smart grids.
A Hybrid Deep Learning Model-based Remaining Useful Life Estimation for Reed Relay with Degradation Pattern Clustering
To provide accurate remaining useful life (RUL) estimation for reed relay, a hybrid deep learning network with degradation pattern clustering is proposed based on the following three considerations.
Energy-Efficient Cell-Free Network Assisted by Hybrid RISs
The proposed hybrid RISs schemes can achieve 92% of the sum rate but 188% of EE of active RISs schemes.
Deep Learning-Based Channel Estimation for Double-RIS Aided Massive MIMO System
Reconfigurable Intelligent Surface (RIS) is considered as an energy-efficient solution for future wireless communication networks due to its fast and low-cost configuration.
Clustering and Analysis of GPS Trajectory Data using Distance-based Features
We propose a new mobility metric, Daily Characteristic Distance, and use it to generate features for each user together with Origin-Destination matrix features.
Holographic MIMO Communications: Theoretical Foundations, Enabling Technologies, and Future Directions
In this survey, we present a comprehensive overview of the latest advances in the HMIMO communications paradigm, with a special focus on their physical aspects, their theoretical foundations, as well as the enabling technologies for HMIMO systems.
Digital Twin for Real-time Li-ion Battery State of Health Estimation with Partially Discharged Cycling Data
To meet the fairly high safety and reliability requirements in practice, the state of health (SOH) estimation of Lithium-ion batteries (LIBs), which has a close relationship with the degradation performance, has been extensively studied with the widespread applications of various electronics.
Algorithm Unrolling-Based Distributed Optimization for RIS-Assisted Cell-Free Networks
To improve the efficiency of the D-ADMM in distributed BSs, we develop a monodirectional information exchange strategy with a small signaling overhead.
Cooperative Beamforming and RISs Association for Multi-RISs Aided Multi-Users MmWave MIMO Systems through Graph Neural Networks
Reconfigurable intelligent surface (RIS) is considered as a promising solution for next-generation wireless communication networks due to a variety of merits, e. g., customizing the communication environment.
Spatiotemporal Capsule Neural Network for Vehicle Trajectory Prediction
An accurate vehicle trajectory prediction benefits communication traffic management and network resource allocation for the real-time application of the V2X network.
A Generalized Electromagnetic-Domain Channel Modeling for LOS Holographic MIMO with Arbitrary Surface Placements
Holographic multiple-input multiple-output (H-MIMO) is considered as one of the most promising technologies to enable future wireless communications in supporting the expected extreme requirements, such as high energy and spectral efficiency.
Robust mmWave Beamforming by Self-Supervised Hybrid Deep Learning
Beamforming with large-scale antenna arrays has been widely used in recent years, which is acknowledged as an important part in 5G and incoming 6G.
A Slow-Shifting Concerned Machine Learning Method for Short-term Traffic Flow Forecasting
However, a crucial challenge in traffic flow forecasting is the slow shifting in temporal peaks between daily and weekly cycles, resulting in the nonstationarity of the traffic flow signal and leading to difficulty in accurate forecasting.
Lithium-ion Battery Online Knee Onset Detection by Matrix Profile
Lithium-ion batteries (LiBs) degrade slightly until the knee onset, after which the deterioration accelerates to end of life (EOL).
Holographic MIMO Communications with Arbitrary Surface Placements: Near-Field LoS Channel Model and Capacity Limit
Envisioned as one of the most promising technologies, holographic multiple-input multiple-output (H-MIMO) recently attracts notable research interests for its great potential in expanding wireless possibilities and achieving fundamental wireless limits.
Environment-Aware Codebook for Reconfigurable Intelligent Surface-Aided MISO Communications
Reconfigurable intelligent surface (RIS) is a revolutionary technology that can customize the wireless channel and improve the energy efficiency of next-generation cellular networks.
Semi-Supervised RF Fingerprinting with Consistency-Based Regularization
As a promising non-password authentication technology, radio frequency (RF) fingerprinting can greatly improve wireless security.
A Federated Learning-based Industrial Health Prognostics for Heterogeneous Edge Devices using Matched Feature Extraction
The algorithm searches across the heterogeneous locally trained models and matches neurons with probabilistically similar feature extraction functions first, before selectively averaging them to form the federated model parameters.
Attack-Resilient Design for Connected and Automated Vehicles
Given enough system knowledge, adversaries are still able to launch a range of attacks that can surpass the detection scheme by hiding within the system disturbances and uncertainty -- we refer to this class of attacks as \textit{stealthy FDI attacks}.
Radio Generation Using Generative Adversarial Networks with An Unrolled Design
Experimental results with extensive simulations demonstrate that our proposed GAN framework can effectively learn transmitter characteristics and various channel effects, thus accurately modeling for an underlying sampling distribution to synthesize radio signals of high quality.
Towards Ubiquitous Semantic Metaverse: Challenges, Approaches, and Opportunities
In recent years, ubiquitous semantic Metaverse has been studied to revolutionize immersive cyber-virtual experiences for augmented reality (AR) and virtual reality (VR) users, which leverages advanced semantic understanding and representation to enable seamless, context-aware interactions within mixed-reality environments.
A Transmit-Receive Parameter Separable Electromagnetic Channel Model for LoS Holographic MIMO
To support the extremely high spectral efficiency and energy efficiency requirements, and emerging applications of future wireless communications, holographic multiple-input multiple-output (H-MIMO) technology is envisioned as one of the most promising enablers.
Enhancing Near-Field Sensing and Communications with Sparse Arrays: Potentials, Challenges, and Emerging Trends
Nevertheless, XL-arrays introduce deviations in electromagnetic propagation compared to traditional arrays, fundamentally challenging the assumption with the planar-wave model.
Joint Power and 3D Trajectory Optimization for UAV-enabled Wireless Powered Communication Networks with Obstacles
For UTTOP, we first introduce a pretreatment method, and then use an improved particle swarm optimization with Normal distribution initialization, Genetic mechanism, Differential mechanism and Pursuit operator (PSO-NGDP) to deal with this sub optimization problem.
Learning Decentralized Traffic Signal Controllers with Multi-Agent Graph Reinforcement Learning
Nevertheless, existing MARL algorithms ignore effective information aggregation which is fundamental for improving the learning capacity of decentralized agents.
Joint User Association, Interference Cancellation and Power Control for Multi-IRS Assisted UAV Communications
To address the aforementioned challenges, we propose a new optimization algorithm for joint IRS-user association, trajectory optimization of UAVs, successive interference cancellation (SIC) decoding order scheduling and power allocation to maximize system energy efficiency.
LightGCNet: A Lightweight Geometric Constructive Neural Network for Data-Driven Soft sensors
Herein, guided by spatial geometric, a lightweight geometric constructive neural network, namely LightGCNet, is proposed, which utilizes compact angle constraint to assign the hidden parameters from dynamic intervals.
CRB Minimization for RIS-aided mmWave Integrated Sensing and Communications
In this paper, reconfigurable intelligent surface (RIS) is employed in a millimeter wave (mmWave) integrated sensing and communications (ISAC) system.
A Change Point Detection Integrated Remaining Useful Life Estimation Model under Variable Operating Conditions
During online monitoring, the temporal correlation dynamics of a query device is monitored for breach of the control limit derived in offline training.
Distributed Task-Oriented Communication Networks with Multimodal Semantic Relay and Edge Intelligence
In this article, we present a novel framework, named distributed task-oriented communication networks (DTCN), based on recent advances in multimodal semantic transmission and edge intelligence.
Graph Attention-based Reinforcement Learning for Trajectory Design and Resource Assignment in Multi-UAV Assisted Communication
In this paper, a novel graph-attention multi-agent trust region (GA-MATR) reinforcement learning framework is proposed to solve the multi-UAV assisted communication problem.
RIS-empowered Topology Control for Distributed Learning in Urban Air Mobility
Urban Air Mobility (UAM) expands vehicles from the ground to the near-ground space, envisioned as a revolution for transportation systems.
RIS-Enabled Joint Near-Field 3D Localization and Synchronization in SISO Multipath Environments
Reconfigurable Intelligent Surfaces (RIS) show great promise in the realm of 6th generation (6G) wireless systems, particularly in the areas of localization and communication.
Near-Field Channel Modeling for Holographic MIMO Communications
Empowered by the latest progress on innovative metamaterials/metasurfaces and advanced antenna technologies, holographic multiple-input multiple-output (H-MIMO) emerges as a promising technology to fulfill the extreme goals of the sixth-generation (6G) wireless networks.
TJCCT: A Two-timescale Approach for UAV-assisted Mobile Edge Computing
Since the problem is a non-convex and NP-hard mixed integer nonlinear programming (MINLP), we propose a two-timescale joint computing resource allocation, computation offloading, and trajectory control (TJCCT) approach for solving the problem.
Computation Offloading for Multi-server Multi-access Edge Vehicular Networks: A DDQN-based Method
In this paper, we investigate a multi-user offloading problem in the overlapping domain of a multi-server mobile edge computing system.
