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Found 19 papers, 7 papers with code
Wireless Channel Prediction via Gaussian Mixture Models
In this work, we utilize a Gaussian mixture model (GMM) to capture the underlying probability density function (PDF) of the channel trajectories of moving mobile terminals (MTs) within the coverage area of a base station (BS) in an offline phase.
A Low-Complexity Machine Learning Design for mmWave Beam Prediction
The 3rd Generation Partnership Project (3GPP) is currently studying machine learning (ML) for the fifth generation (5G)-Advanced New Radio (NR) air interface, where spatial and temporal-domain beam prediction are important use cases.
Digital Twin of the Radio Environment: A Novel Approach for Anomaly Detection in Wireless Networks
The increasing relevance of resilience in wireless connectivity for Industry 4. 0 stems from the growing complexity and interconnectivity of industrial systems, where a single point of failure can disrupt the entire network, leading to significant downtime and productivity losses.
Waveforms for sub-THz 6G: Design Guidelines
The projected sub-THz (100 - 300 GHz) part of the upcoming 6G standard will require a careful design of the waveform and choice of slot structure.
Machine Learning for QoS Prediction in Vehicular Communication: Challenges and Solution Approaches
This proactive behavior of the network can be leveraged to sustain, for example, a specific quality of service requirement.
Explainable Artificial Intelligence (XAI)
Feature Engineering
Berlin V2X: A Machine Learning Dataset from Multiple Vehicles and Radio Access Technologies
The evolution of wireless communications into 6G and beyond is expected to rely on new machine learning (ML)-based capabilities.
Toward an AI-enabled Connected Industry: AGV Communication and Sensor Measurement Datasets
This paper presents two wireless measurement campaigns in industrial testbeds: industrial Vehicle-to-vehicle (iV2V) and industrial Vehicle-to-infrastructure plus Sensor (iV2I+), together with detailed information about the two captured datasets.
A Novel Approach for Cancellation of Non-Aligned Inter Spreading Factor Interference in LoRa Systems
In this paper, we analytically model this interference, and propose an interference cancellation method based on the idea of segmentation of the received signal.
CNN aided Weighted Interpolation for Channel Estimation in Vehicular Communications
IEEE 802. 11p standard defines wireless technology protocols that enable vehicular transportation and manage traffic efficiency.
Channel Estimation for MIMO Space Time Coded OTFS under Doubly Selective Channels
The OTFS modulation has been recently proposed as a robust technique under time varying channels due to its property of spreading the data symbols over time and frequency.
OFDM with Index Modulation in Orbital Angular Momentum Multiplexed Free Space Optical Links
Communication using orbital angular momentum (OAM) modes has recently received a considerable interest in free space optical (FSO) communications.
Alternative Chirp Spread Spectrum Techniques for LPWANs
Chirp spread spectrum (CSS) is the modulation technique currently employed by Long-Range (LoRa), which is one of the most prominent Internet of things wireless communications standards.
Context-Aware Security for 6G Wireless The Role of Physical Layer Security
Sixth generation systems are expected to face new security challenges, while opening up new frontiers towards context awareness in the wireless edge.
Cryptography and Security Signal Processing
Joint TRFI and Deep Learning for Vehicular Channel Estimation
IEEE 802. 11p standard enables the wireless technology that defines vehicular communications.
Adaptive Channel Estimation based on Deep Learning
Channel state information is very critical in various applications such as physical layer security, indoor localization, and channel equalization.
In-phase and Quadrature Chirp Spread Spectrum for IoT Communications
In this paper, we propose a scheme that encodes information bits on both in-phase and quadrature components of the chirp signal, and rather employs a coherent detector at the receiver.
Enhancing Least Square Channel Estimation Using Deep Learning
Least square (LS) channel estimation employed in various communications systems suffers from performance degradation especially in low signal-to-noise ratio (SNR) regions.
Deep Learning Based Channel Estimation Schemes for IEEE 802.11p Standard
IEEE 802. 11p standard is specially developed to define vehicular communications requirements and support cooperative intelligent transport systems.
Network Massive MIMO Transmission Over Millimeter-Wave and Terahertz Bands: Mobility Enhancement and Blockage Mitigation
Based on these insights, the network massive MIMO precoding design is reduced to a network sum-rate maximization problem with respect to beam domain power allocation.
