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Found 19 papers, 0 papers with code
A Variational Auto-Encoder Enabled Multi-Band Channel Prediction Scheme for Indoor Localization
Indoor localization is getting increasing demands for various cutting-edged technologies, like Virtual/Augmented reality and smart home.
High-Performance Transmission Mechanism Design of Multi-Stream Carrier Aggregation for 5G Non-Standalone Network
Multi-stream carrier aggregation is a key technology to expand bandwidth and improve the throughput of the fifth-generation wireless communication systems.
Prediction-based Hybrid Slicing Framework for Service Level Agreement Guarantee in Mobility Scenarios: A Deep Learning Approach
In the proposal, LSTM networks are employed to predict traffic demand and the location of each user in a slicing window level.
Joint Optimization of DNN Inference Delay and Energy under Accuracy Constraints for AR Applications
The high computational complexity and high energy consumption of artificial intelligence (AI) algorithms hinder their application in augmented reality (AR) systems.
High Precision Indoor Localization with Dummy Antennas -- An Experimental Study
With the rising demand for indoor localization, high precision technique-based fingerprints became increasingly important nowadays.
A Novel GCN based Indoor Localization System with Multiple Access Points
With the rapid development of indoor location-based services (LBSs), the demand for accurate localization keeps growing as well.
Arbitrary-Shaped Text Detection withAdaptive Text Region Representation
In this paper, we propose a novel text regionrepresentation method, with a robust pipeline, which can precisely detect dense adjacent text instances witharbitrary shapes.
Self-Calibrating Indoor Localization with Crowdsourcing Fingerprints and Transfer Learning
Precise indoor localization is one of the key requirements for fifth Generation (5G) and beyond, concerning various wireless communication systems, whose applications span different vertical sectors.
Energy-Efficient NOMA Multicasting System for 5G Cellular V2X Communications with Imperfect CSI
The proposed system multicast the information through low complexity optimal power allocation algorithms used under channel outage probability constraint of vehicles with imperfect CSI, QoS constraints of vehicles, and transmit power limits constraint of RSUs.
Joint Visual and Wireless Signal Feature based Approach for High-Precision Indoor Localization
The existing localization systems for indoor applications basically rely on wireless signal.
High Accurate Time-of-Arrival Estimation with Fine-Grained Feature Generation for Internet-of-Things Applications
Conventional schemes often require extra reference signals or more complicated algorithms to improve the time-of-arrival (TOA) estimation accuracy.
Cooling-Aware Resource Allocation and Load Management for Mobile Edge Computing Systems
Driven by explosive computation demands of Internet of Things (IoT), mobile edge computing (MEC) provides a promising technique to enhance the computation capability for mobile users.
Deep Learning based OTDOA Positioning for NB-IoT Communication Systems
Positioning is becoming a key component in many Internet of Things (IoT) applications.
Age of Information Optimized MAC in V2X Sidelink via Piggyback-Based Collaboration
Real-time status update in future vehicular networks is vital to enable control-level cooperative autonomous driving.
Information Theory Networking and Internet Architecture Information Theory
Deep Reinforcement Learning-Based Beam Tracking for Low-Latency Services in Vehicular Networks
Ultra-Reliable and Low-Latency Communications (URLLC) services in vehicular networks on millimeter-wave bands present a significant challenge, considering the necessity of constantly adjusting the beam directions.
Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion
Environmental Sound Classification (ESC) is an important and challenging problem, and feature representation is a critical and even decisive factor in ESC.
Attention based Convolutional Recurrent Neural Network for Environmental Sound Classification
In order to deal with this, we employ a frame-level attention model to focus on the semantically relevant frames and salient frames.
Passive TCP Identification for Wired and WirelessNetworks: A Long-Short Term Memory Approach
TCP congestion control algorithm identification (TCP identification) can be used to significantly improve network efficiency.
How many labeled license plates are needed?
As a large amount of labeled data is typically difficult to collect and even more difficult to annotate, data augmentation and data generation are widely used in the process of training deep neural networks.
