111 citations · 317 across the 22 of their papers we have counts for
23 papers
Designing, Deployment and Field Testing of C2Stack for Networked Intelligent Software-Defined UAVs
Maxwell McManus, Zhaoxi Zhang, Sidharth Santhi Nivas +8
Unmanned Aerial Vehicles (UAVs) are emerging as critical enablers of next-generation wireless networking and autonomous systems. Despite their potential, deploying and testing netw…
StormWave: An Open-Source Portable SDR Platform for Over-the-Air Resilience Evaluation of Terrestrial and Aerial Communications
Yuqing Cui, Zhaoxi Zhang, Sidharth Santhi Nivas +9
This paper presents \emph{StormWave}, an open-source, portable software-defined Radio Frequency (RF) interference generation and monitoring platform designed for realistic field-ba…
C-POD: An AWS Cloud Framework for Edge Pod Automation and Remote Wireless Testbed Sharing
Annoy Dey, Vineet Sreeram, Gokkul Eraivan Arutkani Aiyanathan +6
This paper presents C-POD, a cloud-native framework that automates the deployment and management of edge pods for seamless remote access and sharing of wireless testbeds. C-POD lev…
BenchLink: An SoC-Based Benchmark for Resilient Communication Links in GPS-Denied Environments
Sidharth Santhi Nivas, Prem Sagar Pattanshetty Vasanth Kumar, Zhaoxi Zhang +7
Accurate timing and synchronization, typically enabled by GPS, are essential for modern wireless communication systems. However, many emerging applications must operate in GPS-deni…
Cross-Layer Design for Near-Field mmWave Beam Management and Scheduling under Delay-Sensitive Traffic
Zijun Wang, Anjali Omer, Jacob Chakareski +2
Next-generation wireless networks will rely on mmWave/sub-THz spectrum and extremely large antenna arrays (ELAAs). This will push their operation into the near field where far-fiel…
ASL360: AI-Enabled Adaptive Streaming of Layered 360 Video over UAV-assisted Wireless Networks
Alireza Mohammadhosseini, Jacob Chakareski, Nicholas Mastronarde
We propose ASL360, an adaptive deep reinforcement learning-based scheduler for on-demand 360 video streaming to mobile VR users in next generation wireless networks. We aim…
On the Effects of Modeling on the Sim-to-Real Transfer Gap in Twinning the POWDER Platform
Maxwell McManus, Yuqing Cui, Zhaoxi Zhang +4
Digital Twin (DT) technology is expected to play a pivotal role in NextG wireless systems. However, a key challenge remains in the evaluation of data-driven algorithms within DTs,…
Cloud-Based Federation Framework and Prototype for Open, Scalable, and Shared Access to NextG and IoT Testbeds
Maxwell McManus, Tenzin Rinchen, Annoy Dey +9
In this work, we present a new federation framework for UnionLabs, an innovative cloud-based resource-sharing infrastructure designed for next-generation (NextG) and Internet of Th…
Spectrum Coexistence of Satellite-borne Passive Radiometry and Terrestrial Next-G Networks
Mohammad Koosha, Nicholas Mastronarde
Spectrum coexistence between terrestrial Next-G cellular networks and space-borne remote sensing (RS) is now gaining attention. One major question is how this would impact RS equip…
Coexistence of Satellite-borne Passive Radiometry and Terrestrial NextG Wireless Networks in the Restricted L-Band
Mohammad Koosha, Nicholas Mastronarde
The rapid growth of active wireless communications technologies has fostered research on spectrum coexistence worldwide. One idea that is gaining attention is sharing frequency ban…
minimizing estimation error variance using a weighted sum of samples from the soil moisture active passive (SMAP) satellite
Mohammad Koosha, Nicholas Mastronarde
The National Aeronautics and Space Administration's (NASA) Soil Moisture Active Passive (SMAP) is the latest passive remote sensing satellite operating in the protected L-band spec…
Digital Twin-Enabled Domain Adaptation for Zero-Touch UAV Networks: Survey and Challenges
Maxwell McManus, Yuqing Cui, Josh +7
In existing wireless networks, the control programs have been designed manually and for certain predefined scenarios. This process is complicated and error-prone, and the resulting…
Estimation of Individual Treatment Effect in Latent Confounder Models via Adversarial Learning
Changhee Lee, Nicholas Mastronarde, Mihaela van der Schaar
Estimating the individual treatment effect (ITE) from observational data is essential in medicine. A central challenge in estimating the ITE is handling confounders, which are fact…
What is Interpretable? Using Machine Learning to Design Interpretable Decision-Support Systems
Owen Lahav, Nicholas Mastronarde, Mihaela van der Schaar
Recent efforts in Machine Learning (ML) interpretability have focused on creating methods for explaining black-box ML models. However, these methods rely on the assumption that sim…
Accelerated Structure-Aware Reinforcement Learning for Delay-Sensitive Energy Harvesting Wireless Sensors
Nikhilesh Sharma, Nicholas Mastronarde, Jacob Chakareski
We investigate an energy-harvesting wireless sensor transmitting latency-sensitive data over a fading channel. The sensor injects captured data packets into its transmission queue…
Structural Properties of Optimal Transmission Policies for Delay-Sensitive Energy Harvesting Wireless Sensors
Nikhilesh Sharma, Nicholas Mastronarde, Jacob Chakareski
We consider an energy harvesting sensor transmitting latency-sensitive data over a fading channel. We aim to find the optimal transmission scheduling policy that minimizes the pack…
Improving the Coverage and Spectral Efficiency of Millimeter-Wave Cellular Networks using Device-to-Device Relays
Shuanshuan Wu, Rachad Atat, Nicholas Mastronarde +1
The susceptibility of millimeter waveform propagation to blockages limits the coverage of millimeter-wave (mmWave) signals. To overcome blockages, we propose to leverage two-hop de…
UB-ANC Drone: A Flexible Airborne Networking and Communications Testbed
Jalil Modares, Nicholas Mastronarde
We present the University at Buffalo's Airborne Networking and Communications Testbed (UB-ANC Drone). UB-ANC Drone is an open software/hardware platform that aims to facilitate rap…
To Relay or Not to Relay: Learning Device-to-Device Relaying Strategies in Cellular Networks
Nicholas Mastronarde, Viral Patel, Jie Xu +2
We consider a cellular network where mobile transceiver devices that are owned by self-interested users are incentivized to cooperate with each other using tokens, which they excha…
Markov Decision Process Based Energy-Efficient On-Line Scheduling for Slice-Parallel Video Decoders on Multicore Systems
Nicholas Mastronarde, Karim Kanoun, David Atienza +2
We consider the problem of energy-efficient on-line scheduling for slice-parallel video decoders on multicore systems. We assume that each of the processors are Dynamic Voltage Fre…
Transmitting important bits and sailing high radio waves: a decentralized cross-layer approach to cooperative video transmission
Nicholas Mastronarde, Francesco Verde, Donatella Darsena +2
We investigate the impact of cooperative relaying on uplink and downlink multi-user (MU) wireless video transmissions. The objective is to maximize the long-term sum of utilities a…
Fast Reinforcement Learning for Energy-Efficient Wireless Communications
Nicholas Mastronarde, Mihaela van der Schaar
We consider the problem of energy-efficient point-to-point transmission of delay-sensitive data (e.g. multimedia data) over a fading channel. Existing research on this topic utiliz…
Online Reinforcement Learning for Dynamic Multimedia Systems
Nicholas Mastronarde, Mihaela van der Schaar
In our previous work, we proposed a systematic cross-layer framework for dynamic multimedia systems, which allows each layer to make autonomous and foresighted decisions that maxim…