A5058335425- Wireless Signal Modulation Classification
- IoT and Edge/Fog Computing
- Energy Harvesting in Wireless Networks
- Millimeter-Wave Propagation and Modeling
- Indoor and Outdoor Localization Technologies
- Advanced MIMO Systems Optimization
- Wireless Communication Security Techniques
- Wireless Networks and Protocols
- Software-Defined Networks and 5G
- Full-Duplex Wireless Communications
- Internet Traffic Analysis and Secure E-voting
- Energy Efficient Wireless Sensor Networks
- Advanced Neural Network Applications
- Cooperative Communication and Network Coding
- Network Security and Intrusion Detection
- Age of Information Optimization
- UAV Applications and Optimization
- Cognitive Radio Networks and Spectrum Sensing
- Speech and Audio Processing
- Radar Systems and Signal Processing
- IoT Networks and Protocols
- Adversarial Robustness in Machine Learning
- Mobile Crowdsensing and Crowdsourcing
- Mobile Ad Hoc Networks
- Microwave Engineering and Waveguides
Northeastern University
2017-2025
Boston University
2019-2024
University of California, San Diego
2024
Universidad del Noreste
2019-2023
Association for Computing Machinery
2020
Missouri University of Science and Technology
2013-2016
University of Pisa
2012
National Research Council
2012
The Internet of Things (IoT) realizes a vision where billions interconnected devices are deployed just about everywhere, from inside our bodies to the most remote areas globe. As IoT will soon pervade every aspect lives and be accessible anywhere, addressing critical security threats is now more important than ever. Traditional approaches applied as an afterthought "patch" against known attacks insufficient. Indeed, next-generation challenges require new secure-by-design vision, addressed...
Radio fingerprinting uniquely identifies wireless devices by leveraging tiny hardware-level imperfections inevitably present in off-the-shelf radio circuitry. This way, can be directly identified at the physical layer analyzing unprocessed received waveform - thus avoiding energy-expensive upper-layer cryptography that resource-challenged embedded may not able to afford. Recent advances have proven convolutional neural networks (CNNs) thanks their multidimensional mappings achieve accuracy...
Radio fingerprinting provides a reliable and energy-efficient IoT authentication strategy by leveraging the unique hardware-level imperfections imposed on received wireless signal transmitter's radio circuitry. Most of existing approaches utilize hand-tailored protocol-specific feature extraction techniques, which can identify devices operating under pre-defined protocol only. Conversely, mapping inputs onto very large space, deep learning algorithms be trained to fingerprint populations any...
The notions of softwarization and virtualization the radio access network (RAN) next-generation (5G) wireless systems are ushering in a vision where applications services physically decoupled from devices infrastructure. This crucial aspect will ultimately enable dynamic deployment heterogeneous by different operators over same physical RAN slicing is form 5G that allows infrastructure owners to dynamically “slice” “serve” their resources (i. e., spectrum, power, antennas, among others)...
Colosseum is an open-access and publicly-available large-scale wireless testbed for experimental research via virtualized softwarized waveforms protocol stacks on a fully programmable, "white-box" platform. Through 256 state-of-the-art software-defined radios massive channel emulator core, can model virtually any scenario, enabling the design, development testing of solutions at scale in variety deployments conditions. These radio-frequency scenarios are reproduced through high-fidelity...
The unprecedented requirements of IoT have made fine-grained optimization spectrum resources an urgent necessity. Thus, designing techniques able to extract knowledge from the in real time and select optimal access strategy accordingly has become more important than ever. Moreover, 5G networks will require complex management schemes deal with problems such as adaptive beam rate selection. Although deep learning (DL) been successful modeling phenomena, commercially available wireless devices...
The Long Range (LoRa) protocol for low-power wide-area networks (LPWANs) is a strong candidate to enable the massive roll-out of Internet Things (IoT) because its low cost, impressive sensitivity (-137dBm), and scalability potential. As tens thousands tiny LoRa devices are deployed over large geographic areas, key component success will be development reliable robust authentication mechanisms. To this end, Radio Frequency Fingerprinting (RFFP) through deep learning (DL) has been heralded as...
Today's radio access networks (RANs) are monolithic entities which often operate statically on a given set of parameters for the entirety their operations. To implement realistic and effective spectrum sharing policies, RANs will need to seamlessly intelligently change operational parameters. In stark contrast with existing paradigms, new O-RAN architectures 5G-and-beyond (NextG) separate logic that controls RAN from its hardware substrate, allowing unprecedented real-time fine-grained...
Conventionally, Wi-Fi radio signals are widely used for data transmissions in a wireless local area network (WLAN). Recently, it has been an interesting topic to also apply sense the environment where these propagate and identify changes associated with certain activities. This technique is referred as sensing, proven effective variety of use cases, such proximity detection, gesture recognition, target counting, health monitoring. As result, IEEE 802.11 working group formed new Task Group,...
Although mission-critical applications require the use of deep neural networks (DNNs), their continuous execution at mobile devices results in a significant increase energy consumption. While edge offloading can decrease consumption, erratic patterns channel quality, network and server load lead to severe disruption system's key operations. An alternative approach, called split computing, generates compressed representations within model (called "bottlenecks"), reduce bandwidth usage Prior...
As Wi-Fi becomes ubiquitous in public and private spaces, it natural to leverage its intrinsic ability sense the surrounding environment implement groundbreaking wireless sensing applications such as human presence detection, activity recognition, object tracking. For this reason, IEEE 802.11bf Task Group is defining appropriate modifications existing standards enhance capabilities through 802.11-compliant devices. However, new standard expected leave specific algorithms open implementation....
Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges RAN that it provably NP-Hard problem. For this reason, we design near-optimal low-complexity distributed algorithms. First, model problem as a congestion game, and demonstrate such game admits unique <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Nash equilibrium</i> (NE). Then, evaluate...
Mobile crowdsensing harnesses the sensing power of modern smartphones to collect and analyze data beyond scale what was previously possible with traditional sensor networks. Given participatory nature mobile crowdsensing, it is imperative incentivize users provide services in a timely reliable manner. Most importantly, given sensed information often valid for limited period time, capability smartphone execute tasks largely depends on their mobility pattern, which uncertain. For this reason,...
The explosion of 5G networks and the Internet Things will result in an exceptionally crowded RF environment, where techniques such as spectrum sharing dynamic access become essential components wireless communication process. In this vision, devices must be able to (i) learn autonomously extract knowledge from on-the-fly; (ii) react real time inferred by appropriately changing parameters, including frequency band, symbol modulation, coding rate, among others. Traditional CPU-based machine...
Network slicing of multi-access edge computing (MEC) resources is expected to be a pivotal technology the success 5G networks and beyond. The key challenge that sets MEC apart from traditional resource allocation problems nodes depend on tightly-intertwined strictly-constrained networking, computation storage resources. Therefore, instantiating slices without incurring in over-provisioning hardly addressable with existing algorithms. main innovation this paper Sl-EDGE, unified framework...
Abstract Sixth-generation wireless networks will aggregate higher-than-ever mobile traffic into ultra-high capacity backhaul links, which could be deployed on the largely untapped spectrum above 100 GHz. Current regulations however prevent allocation of large contiguous bands for communications at these frequencies, since several narrow are reserved to protect passive sensing services. These include radio astronomy and Earth exploration satellites using sensors that suffer from harmful...
Thanks to the ubiquitous deployment of Wi-Fi hotspots, channel state information (CSI)-based sensing can unleash game-changing applications in many fields, such as healthcare, security, and entertainment. However, despite one decade active research on sensing, most existing work only considers legacy IEEE 802.11n devices, often particular strictly-controlled environments. Worse yet, there is a fundamental lack understanding impact CSI-based modern features, 160-MHz bandwidth, multiple-input...
5G and beyond cellular networks (NextG) will support the continuous execution of resource-expensive edgeassisted deep learning (DL) tasks.To this end, Radio Access Network (RAN) resources need to be carefully "sliced" satisfy heterogeneous application requirements while minimizing RAN usage.Existing slicing frameworks treat each DL task as equal inflexibly define assign task, which leads sub-optimal performance.In paper, we propose SEM-O-RAN, first semantic flexible framework for NextG Open...