Cognitive Reconfigurable Embedded Systems Lab

Projects

Localization, Beamtraining and Subcarrier to Location Mapping for Near-Field Channels with TTD Arrays

Principal Investigator(s): Danijela Cabric        Student(s): Ibrahim Pehlivan

Near-field beamforming enables beams to be targeted towards a given location, as opposed only to a given angle in traditional far-field beamforming. This capability can allow base stations to serve multiple users simultaneously, even if they are at the same radial angle [1]. This additional degree of freedom, however, increases the already prohibitive beam training […]

0 publication(s)

Deep Learning Aided Wideband Spectrum Sensing and Monitoring

Principal Investigator(s): Danijela Čabrić        Student(s): Tianyi Zhao and Benjamin Domae

An electromagnetic spectrum can reveal the radio frequency (RF) threats in a given geographic location. Detecting and characterizing those RF footprints in the spectrum is essential to improve situational awareness and threat identification, prevention and response. Traditionally, digital signal processing techniques can be utilized for transmission detection, but those methods require prior knowledge about the […]

0 publication(s)

Millimeter Wave Spectrum Sharing using Analog True Time Delay Array based Wideband Nulling

Principal Investigator(s): Danijela Cabric        Student(s): Aditya Wadaskar, Shamik Sarkar

Millimeter wave (mmWave) cellular networks are characterized by dense deployments of base stations and users. Identifying spectrum-sharing opportunities in these bands is of crucial importance to ensure optimal spectrum utilization. However, non-cooperating cellular operators sharing spectral resources suffer from capacity degradation due to wideband interference. Without explicit channel knowledge and coordination across operators, interference suppression […]

0 publication(s)

Sub-band-Multiplexed Multi-User Data Communication in mmWave and THz with Analog True Time Delay Arrays

Principal Investigator(s): Danijela Cabric        Student(s): Aditya Wadaskar, Ibrahim Pehlivan, Ding Zhao

Wideband millimeter-wave (mmWave) and terahertz (THz) systems can facilitate simultaneous data communication with multiple spatially separated users. It is desirable to orthogonalize users across sub-bands by deploying frequency-dependent beams with a sub-band-specific spatial response. True-Time-Delay (TTD) antenna arrays are a promising wideband architecture to implement sub-band-specific dispersion of beams across space using a single radio […]

2 publication(s)

Machine Learning Based Physical Layer and Mobility Management Solutions Towards 6G

Principal Investigator(s): Danijela Čabrić        Student(s): Benjamin Domae, Donar Li, Enes Krijestorac

5G networks and 6G plans are embracing millimeter-wave (mmW) and sub-terrahertz (sub-THz) bands to unlock additional spectrum and to meet rising consumer demand for high-rate, mobile, cellular data. However, wireless systems at these bands face significant technical challenges to achieve their potential capacity and latency. Many of these challenges arise from the large antenna arrays […]

0 publication(s)

Coordinated Beam Discovery, Association, and Handover in Ultra-Dense Millimeter Wave Cellular Networks

Principal Investigator(s): Danijela Čabrić        Student(s): Veljko Boljanovic

In millimeter wave networks, a high density of base stations is required to avoid outages resulting from the propagation loss and signal blockages. In order to compensate for the signal losses, it has been proposed to equip mmW transmitters and receivers with large number of antennas, which enables forming of narrow beams with high beamforming […]

0 publication(s)

True-time-delay Based Mimo System and Testbed for Low-latency Wideband Beam and Interference Management in Millimeter Wave Networks

Principal Investigator(s): Danijela Cabric        Student(s):

https://labs.wsu.edu/systems-on-chip/project/ttdbeammgmt/

1 publication(s)

Hybrid Vehicular and Cloud Distributed Computing

Principal Investigator(s): Danijela Cabric        Student(s): Enes Krijestorac, Ghaith Hattab

In this study, we propose the use of hybrid offloading of computing tasks simultaneously to edge servers (vertical offloading) via LTE communication and to nearby cars (horizontal offloading) via V2V communication, in order to increase the rate at which tasks are processed compared to local processing. Horizontal offloading is enabled by the vehicle cloudification framework, […]

2 publication(s)

Spectrum Sharing for Massive Access in Unlicensed Ultra-Narrowband IoT Systems

Principal Investigator(s): Danijela Cabric        Student(s): Enes Krijestorac, Ghaith Hattab

In this study, we analyze the coexistence capability of UNB networks and their scalability to enable massive access. Ultra-narrowband (UNB) low-power-wireless networks (LPWA) solutions apply the ultra-narrowband transmissions, which enable demodulation at a very low received power.  UNB LPWA networks normally rely on simple ALOHA-like access protocols, where IoT devices avoid associating and synchronizing with […]

4 publication(s)

Deep Learning for Optimal UAV Basestation Placement

Principal Investigator(s): Danijela Cabric        Student(s): Enes Krijestorac, Samer Hanna

Mobile unmanned aerial vehicles (UAVs) acting as basestations can optimize their position to maximize the signal strength to user equipment on the ground.  In this project, we explore two different placement optimization approaches: model-free and model-based.  In the model-free approach, the UAV does not aim to predict the signal strength across the entire optimization space […]

4 publication(s)

Machine Learning for Blind Signal Identification

Principal Investigator(s): Danijela Cabric        Student(s): Samer Hanna and Isha Gonugunta

The widespread deployment of wireless devices poses new challenges in spectrum management. Many types of wireless devices emit signals in the wireless spectrum; Some of these devices send communication signals which might follow one of the many existing standards like WiFi, Zigebee, Bluetooth, LoRaWan. Other devices transmit radar signals which can be continuous wave signals […]

3 publication(s)

Realistic Wireless Communications UAV Simulator

Principal Investigator(s): Danijela Cabric        Student(s): Samer Hanna and Achinthya Poduval

Unmanned aerial vehicles are envisioned as an integral component of future wireless systems. Despite the widespread interest in UAV communications research, UAV experimental evaluation is restricted by existing laws and regulations. These restrictions along with the overheads of deploying UAVs  make simulations the method of choice of many researchers.  However, many of the existing UAV […]

0 publication(s)

UAV Swarms Distributed Beamforming for Range Extension

Principal Investigator(s): Danijela Cabric        Student(s): Samer Hanna, Enes Krijestorac

The mobility and ease of deployment  of unmanned aerial vehicles  lead to their widespread adoption in many applications like wildlife monitoring, search and rescue, and disaster management. Many of these applications require the deployment of a swarm of collaborating UAVs in remote areas with no communications infrastructure. To establish a long range communications link, the […]

4 publication(s)

VANET Design and Simulation for ITS

Principal Investigator(s):        Student(s):
1 publication(s)

Estimation and Characterization of Frequency Hopping Interferers Using Spectral Sensing Techniques

Principal Investigator(s):        Student(s):
3 publication(s)

Weighted Centroid Localization Algorithm: Theoretical Analysis and Distributed Implementation

Principal Investigator(s):        Student(s):
2 publication(s)

Secure Spectrum Sensing in Cognitive Radio Networks

Principal Investigator(s):        Student(s):
7 publication(s)

Reliable Wideband Spectrum Sensing under Strong Interference Environments in Cognitive Radios

Principal Investigator(s):        Student(s):
2 publication(s)

Joint Spectrum Sensing and Medium Access Control

Principal Investigator(s):        Student(s):
2 publication(s)

Self-Healing Mixed-Signal Baseband Processor for Cognitive Radios

Principal Investigator(s):        Student(s):
2 publication(s)

Energy Efficient Blind Automatic Modulation Classification

Principal Investigator(s):        Student(s):
5 publication(s)

Robust Wideband Spectrum Sensing under Interferers

Principal Investigator(s):        Student(s):
2 publication(s)

Massive MIMO in Interference Management in Cognitive Radio Networks

Principal Investigator(s): Danijela Čabrić        Student(s): Shailesh Chaudhari

In coming years, wireless networks have to serve a large number of data hungry devices due to proliferation of new devices and applications every year. Increasing number of wireless devices (users) are competing for physical layer resources, namely time, space and frequency, to download the data required for different applications. In order to serve a […]

4 publication(s)

Load Balancing and Interference Management for Heterogeneous Cellular Networks

Principal Investigator(s): Danijela Čabrić        Student(s): Ghaith Hattab

With the proliferation of wireless devices and the advent of bandwidth hungry applications such as video streaming, cloud-based technologies, etc., incremental improvements to existing networks and architectures such as 4G are insufficient to meet the projected data demands in the next five years. This has called for paradigm shifts in next generation networks, i.e., 5G, […]

5 publication(s)

Dynamic Spectrum Access by Learning Primary Network Topology

Principal Investigator(s): Danijela Čabrić        Student(s): Shailesh Chaudhari, Mihir Laghate

This project focuses on developing cooperative algorithms for the identification of spectrum holes and classification of primary network activity by geographically large-scale cognitive radio networks. The project consists of three parts, namely localization, footprint learning and network topology learning. The knowledge of PU location is required in a cognitive radio (CR) network for advanced spectrum […]

8 publication(s)

Communication and Interference Cancellation with True-Time-Delay Arrays in Millimeter-Wave Networks

Principal Investigator(s): Danijela Cabric        Student(s): Han Yan, Veljko Boljanovic, Aditya Wadaskar

For data communications, antenna arrays must provide high beamforming gain across all frequency components of the transmit and receive signal to efficiently exploit the wide bandwidths available at mmW. However, beam patterns from conventional antenna arrays using phase shifters are frequency dependent in an uncontrollable manner, degrading beamforming gain, beam directionality, and interference cancellation capability. […]

1 publication(s)

Initial Access with True-Time-Delay Arrays in Millimeter-Wave Networks

Principal Investigator(s): Danijela Cabric        Student(s): Han Yan, Veljko Boljanovic, Aditya Wadaskar

Initial access in existing multiple-input multiple-output communication systems is a procedure which aims to achieve synchronization between the base station and the user and to estimate the dominant propagation directions. Traditionally, the directions are found through beam training, an exhaustive channel probing technique which results in a significant control overhead when large antenna arrays and […]

10 publication(s)

Millimeter-Wave Communication: Network Layer Perspective

Principal Investigator(s): Danijela Cabric        Student(s): Veljko Boljanovic

In millimeter wave networks, a high density of base stations is required to avoid outages resulting from the propagation loss and signal blockages. Additionally, base stations and users are equipped with a large number of antennas, which enables forming of narrow beams with high beamforming gains. To achieve a balance between beamforming flexibility and array […]

1 publication(s)

Machine Learning Assisted Beam Training and Tracking

Principal Investigator(s): Danijela Cabric        Student(s): Han Yan, Benjamin Domae, Donar Li

In this project, we aim to reduce the beam alignment overhead for practical mmW communication through novel algorithms that combine compressed sensing and machine learning techniques.  From compressed sensing, we propose pseudorandom beam designs to provide more angle of arrival information from fewer measurements.  We then propose machine learning algorithms to solve for the complex […]

3 publication(s)

Millimeter-wave Signal Processing Algorithm Design

Principal Investigator(s): Danijela Cabric        Student(s): Han Yan, Veljko Boljanovic, Benjamin Domae

Millimeter-wave (mmW) wireless communication will be a key component in the future cellular networks (5G and beyond). High frequency used for mmW systems create unique characteristics and challenges as compared to conventional communication systems below 6GHz. Due to severe propagation loss of the signal, the mmW wireless communication channels have sparse scattering. Furthermore, array architectures […]

9 publication(s)

Millimeter-wave Transceiver and Array Architecture Power-Aware Tradeoffs and Design

Principal Investigator(s): Danijela Cabric        Student(s): Han Yan, Benjamin Domae

Millimeter-wave (mmW) and sub-THz (100-300 GHz) frequencies will be key to the phenomenal data rates promised for future cellular communications (5G and beyond). However, communication systems at mmW/sub-THz frequencies face much larger path loss than conventional communication systems below 6GHz.  To generate sufficient gain to overcome this loss, mmW/sub-THz wireless systems will require large antenna […]

4 publication(s)

Machine Learning for Transmitter Authorization based on RF Fingerprints

Principal Investigator(s): Danijela Cabric        Student(s): Samer Hanna, Samurdhi Karunaratne

With the widespread adoption of the Internet of Things (IoT), the number of wirelessly connected devices will continue to proliferate over the next few years. Along with this increase, device authentication  will become more challenging than ever specially for devices under stringent computation and power budgets.  This calls for passive physical layer based authentication methods […]

9 publication(s)

Improving UAV Swarm Capacity using Distributed MIMO

Principal Investigator(s): Danijela Čabrić        Student(s): Samer Hanna and Enes Krijestorac

Unmanned aerial vehicles are envisioned to be an integral part of future wireless networks. UAV basestations can provide on-demand infrastructure, adapting to spatially and temporally varying user requirements. In scenarios like open air festivals and outdoor markets, a swarm of UAVs can be used to meet user data rate demands. Unlike ground basestations, aerial basestations […]

6 publication(s)