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Found 33 papers, 4 papers with code
Structured Two-Stage True-Time-Delay Array Codebook Design for Multi-User Data Communication
Wideband millimeter-wave and terahertz (THz) systems can facilitate simultaneous data communication with multiple spatially separated users.
A Coordinate Descent Approach to Atomic Norm Minimization
The proposed coordinate descent framework can be readily modified to solve a variety of ANM problems, including multi-dimensional ANM with multiple measurement vectors.
Deep Learning Based Active Spatial Channel Gain Prediction Using a Swarm of Unmanned Aerial Vehicles
We develop novel active prediction approaches which consist of both methods for UAV path planning for optimal measurement collection and methods for prediction of CG across space based on the collected measurements.
RadYOLOLet: Radar Detection and Parameter Estimation Using YOLO and WaveLet
Wavelet-CNN operates on continuous Wavelet transform of the captured signals, and we use it only when RadYOLO fails to detect any radar signal.
ProSpire: Proactive Spatial Prediction of Radio Environment Using Deep Learning
We carefully address several challenges in ProSpire, such as designing a framework that conveniently collects training data for learning, performing the predictions in a fast manner, enabling operations without an area map, and ensuring that the predictions do not lead to undesired interference.
GAN-RXA: A Practical Scalable Solution to Receiver-Agnostic Transmitter Fingerprinting
We also propose two deep-learning approaches (SD-RXA and GAN-RXA) in this first stage to improve the receiver-agnostic property of the RXA framework.
Multiband Massive IoT: A Learning Approach to Infrastructure Deployment
The first approach is based on a predefined model of the environment, while the second approach is measurement-based model-free approach, which is applicable to any environment.
Machine Learning Prediction for Phase-less Millimeter-Wave Beam Tracking
Future wireless networks may operate at millimeter-wave (mmW) and sub-terahertz (sub-THz) frequencies to enable high data rate requirements.
Distributed Transmit Beamforming: Analyzing the Maximum Communication Range
While ideally the maximum range can be trivially calculated from the BF gain, in reality, the BF gain depends on the distance because, at a larger distance, lower SNR of the exchanged preambles causes higher synchronization and phase estimation errors, which in turn degrades the BF gain.
Energy Efficiency Tradeoffs for Sub-THz Multi-User MIMO Base Station Receivers
Sub-terahertz (sub-THz) antenna array architectures significantly impact power usage and communications capacity in multi-user multiple-input multiple-output (MU-MIMO) systems.
Multi-Mode Spatial Signal Processor with Rainbow-like Fast Beam Training and Wideband Communications using True-Time-Delay Arrays
Initial access in millimeter-wave (mmW) wireless is critical toward successful realization of the fifth-generation (5G) wireless networks and beyond.
WiSig: A Large-Scale WiFi Signal Dataset for Receiver and Channel Agnostic RF Fingerprinting
RF fingerprinting leverages circuit-level variability of transmitters to identify them using signals they send.
Wideband Beamforming with Rainbow Beam Training using Reconfigurable True-Time-Delay Arrays for Millimeter-Wave Wireless
The decadal research in integrated true-time-delay arrays have seen organic growth enabling realization of wideband beamformers for large arrays with wide aperture widths.
Real-time Wireless Transmitter Authorization: Adapting to Dynamic Authorized Sets with Information Retrieval
These systems have been shown to offer excellent outlier detection accuracies when trained and tested on a fixed authorized transmitter set.
Distributed Transmit Beamforming: Design and Demonstration from the Lab to UAVs
However, since BF aims to increase the communication range, the individually transmitted preambles are typically at low SNR and their lengths are constrained by the channel coherence time.
Machine Learning Assisted Phase-less Millimeter-Wave Beam Alignment in Multipath Channels
For better scaling with the large arrays required at high mmW bands, compressive sensing methods have been proposed as their overhead scales logarithmically with the array size.
Open Set RF Fingerprinting using Generative Outlier Augmentation
So far, efforts at open set classification have largely relied on the utilization of signal samples captured from a known set of unauthorized transmitters to aid the classifier learn unauthorized transmitter fingerprints.
Rainbow-link: Beam-Alignment-Free and Grant-Free mmW Multiple Access using True-Time-Delay Array
However, due to a limited number of simultaneous beams that can be created with analog/hybrid phased antenna arrays, the overheads of beam training and beam scheduling become a bottleneck for emerging networks that need to support a large number of users and low latency applications.
Destination-Feedback Free Distributed Transmit Beamforming using Guided Directionality
Most existing distributed beamforming approaches rely on the destination radio sending feedback to adjust the transmitters' signals for coherent combining.
Signal Processing Based Deep Learning for Blind Symbol Decoding and Modulation Classification
The estimation results of DPN along with its blind decoding performance are shown to outperform a blind signal processing algorithm for BPSK and QPSK on a simulated dataset.
A 4-Element 800MHz-BW 29mW True-Time-Delay Spatial Signal Processor Enabling Fast Beam-Training with Data Communications
In this work, we demonstrate a true-time-delay (TTD) array with digitally reconfigurable delay elements enabling both fast beam-training at the receiver with wideband data communications.
A Schottky-Diode-Based Wake-Up Receiver for IoT Applications
This design eliminates the area and power dissipation of an external crystal oscillator and only turns on when the second phase is activated.
UAV Swarm Position Optimization for High Capacity MIMO Backhaul
This capacity increase persists when using a massive MIMO ground station.
Spatial Signal Strength Prediction using 3D Maps and Deep Learning
Machine learning (ML) and artificial neural networks (ANNs) have been successfully applied to simulating complex physics by learning physics models thanks to large data.
Band Assignment in Ultra-Narrowband (UNB) Systems for Massive IoT Access
The objective is to find an assignment of BSs to multiplexing bands in order to maximize the packet decoding probability (PDP).
mmRAPID: Machine Learning assisted Noncoherent Compressive Millimeter-Wave Beam Alignment
A key design challenge is to enable rapid beam alignment with phased arrays.
True-Time-Delay Arrays for Fast Beam Training in Wideband Millimeter-Wave Systems
We also propose a suitable algorithm that requires a single pilot to achieve high-accuracy estimation of angle of arrival.
Combining Deep Learning and Linear Processing for Modulation Classification and Symbol Decoding
Deep learning has been recently applied to many problems in wireless communications including modulation classification and symbol decoding.
Open Set Wireless Transmitter Authorization: Deep Learning Approaches and Dataset Considerations
Due to imperfections in transmitters' hardware, wireless signals can be used to verify their identity in an authorization system.
Design of Millimeter-Wave Single-Shot Beam Training for True-Time-Delay Array
Lastly, the study on impairments and required specifications of resolution and range of analog delay taps are used to provide a design insight of energy efficient TTD array, which employs a novel architecture with discrete-time sampling based TTD elements.
Deep Learning Approaches for Open Set Wireless Transmitter Authorization
In this paper, we propose a deep learning approach for transmitter authorization based on open set recognition.
Spectrum Sharing for Massive Access in Ultra-Narrowband IoT Systems
Ultra-narrowband (UNB) communications has become a signature feature for many emerging low-power wide-area (LPWA) networks.
Performance, Power, and Area Design Trade-offs in Millimeter-Wave Transmitter Beamforming Architectures
In this paper, we provide an overview of the state-of-the-art mmWave massive antenna array designs and comparison among three array architectures, namely digital array, partially-connected hybrid array (sub-array), and fully-connected hybrid array.
