
Dimitrios Koutsonikolas
VerifiedNortheastern University · Electrical and Energy Engineering
Active 2005–2026
About
ECE Associate Professor Dimitrios Koutsonikolas was recognized as a Distinguished Member of the Association for Computing Machinery (ACM) for his contributions to improving the performance of millimeter wave networks.
Research topics
- Computer Science
- Computer network
- Operating system
- Artificial Intelligence
- Multimedia
- Real-time computing
- Telecommunications
Selected publications
Performance Characterization of dApps in Open Radio Access Networks
ArXiv.org · 2026-05-06
articleOpen accessDespite recommendations to deploy real-time Open Radio Access Network (O-RAN) applications (dApps) in containerized environments, existing approaches predominantly rely on bare-metal servers. Moreover, current dApp deployments offer limited visibility into the resource usage patterns of both intelligent and non-intelligent dApps, hindering informed deployment decisions. This work addresses these gaps by implementing and evaluating representative dApps across multiple deployment scenarios (bare-metal and containers) to characterize the trade-offs in latency, scalability, and resource utilization. Additionally, we identify key performance bottlenecks and demonstrate how offloading dApps to emerging hardware accelerators, such as smart Network Interface Cards (NICs), can alleviate these limitations and improve real-time responsiveness in O-RAN systems.
Toward Native ISAC Support in O-RAN Architectures for 6G
arXiv (Cornell University) · 2026-03-04
articleOpen accessSenior authorISAC is an emerging paradigm in 6G networks that enables environmental sensing using wireless communication infrastructure. Current O-RAN specifications lack the architectural primitives for sensing integration: no service models expose physical-layer observables, no execution frameworks support sub-millisecond sensing tasks, and fronthaul interfaces cannot correlate transmitted waveforms with their reflections. This article proposes three extensions to O-RAN for monostatic sensing, where transmission and reception are co-located at the base station. First, we specify sensing dApps at the O-DU that process IQ samples to extract delay, Doppler, and angular features. Second, we define E2SM-SENS, a service model enabling xApps to subscribe to sensing telemetry with configurable periodicity. Third, we identify required Open Fronthaul metadata for waveform-echo association. We validate the architecture through a prototype implementation using beamforming and Full-Duplex operation, demonstrating closed-loop control with median end-to-end latency suitable for near-real-time sensing applications. While focused on monostatic configurations, the proposed interfaces extend to bistatic and cooperative sensing scenarios.
Materials Science and Engineering B · 2026-01-12
articleOpen accessAs the world moves toward a low–carbon future, hydrogen (H 2 ) is playing a key role in sustainable energy strategies, driving research into the development of efficient H 2 separation systems. In this study, a scalable low–temperature (250 °C) chemical vapor deposition (CVD) method using tetraethoxysilane (TEOS) and oxygen was employed to deposit a H 2 –selective silica layer on a commercial titania membrane. In contrast to conventional single-stage CVD routes, a novel addition of intermediate ozone (O₃) treatments between deposition steps promoted the formation of a stable, purely inorganic structure by decomposing residual organics and activating the surface for the subsequent deposition. The resulting SiO 2 /TiO 2 membrane demonstrated a favorable balance between permeance and selectivity, achieving a H 2 permeance of 1.9 × 10 – 7 mol m −2 s −1 Pa −1 and a H 2 /CO 2 permselectivity of 80.4 at 250 °C. Additionally, a theoretical mass transport model was applied at each modification stage to assess pore structure evolution, identify the dominant transport mechanisms, and advance the understanding of structure–permeation relationship. • A hydrogen – selective silica layer was deposited on a commercial titania membrane. • The membrane demonstrated a favorable balance between H 2 permeance and selectivity. • Chemical vapor deposition was assisted by ozone post-treatments, performed in stages. • Mass transport model assessed pore-size distributions monitoring structural evolution. • Model validated and predicted transport mechanism contributions for six pure gases.
Who Knows What? Semantic Negotiation for Human-Supervised RAN Agentic Coordination
2026-02-25
articleOpen accessSenior author6G networks promise AI-native RAN architectures that autonomously coordinate applications and infrastructure. Yet a critical gap remains: applications know their constraints (battery-critical mission, safety deadlines) but not network state (cell load, coverage); the RAN knows wireless conditions but not application needs. Static policies ignore context, autonomous ML lacks explainability, manual coordination does not scale.
Demo: Immersive Network Operations using 5G-Enabled XR Headsets and MCP
2026-02-25
articleOpen accessSenior authorWe demonstrate a fully voice-driven troubleshooting assistant for 5G edge networks using XR headsets with integrated 5G connectivity. The human operator describes symptoms and navigates diagnostics entirely through speech; the LLM responds via synthesized voice while simultaneously rendering relevant metrics as AR overlays. This multimodal feedback, audio explanation paired with visual data, enables hands-free, eyes-free operation in isolated field environments where traditional interfaces are impractical
Poster: Bridging the Gap: E2SM-SENS for ISAC-Native O-RAN Architectures
2026-02-25
articleOpen accessSenior authorIntegrated Sensing and Communication (ISAC) enables 6G networks to perform environmental sensing using communication infrastructure. We propose O-RAN extensions for monostatic sensing: (1) sensing dApps at the O-DU for IQ processing; (2) E2SM-SENS, a service model for sensing telemetry. Prototype evaluation demonstrates closed-loop latencies compatible with vehicular perception and UAV tracking use cases.
Disentangling the Throughput Contributions of MIMO and Carrier Aggregation in 5G Networks
Lecture notes in computer science · 2026-01-01
book-chapterSenior authorPerformance Characterization of dApps in Open Radio Access Networks
arXiv (Cornell University) · 2026-05-06
preprintOpen accessDespite recommendations to deploy real-time Open Radio Access Network (O-RAN) applications (dApps) in containerized environments, existing approaches predominantly rely on bare-metal servers. Moreover, current dApp deployments offer limited visibility into the resource usage patterns of both intelligent and non-intelligent dApps, hindering informed deployment decisions. This work addresses these gaps by implementing and evaluating representative dApps across multiple deployment scenarios (bare-metal and containers) to characterize the trade-offs in latency, scalability, and resource utilization. Additionally, we identify key performance bottlenecks and demonstrate how offloading dApps to emerging hardware accelerators, such as smart Network Interface Cards (NICs), can alleviate these limitations and improve real-time responsiveness in O-RAN systems.
Toward Native ISAC Support in O-RAN Architectures for 6G
Open MIND · 2026-03-04
preprintSenior authorISAC is an emerging paradigm in 6G networks that enables environmental sensing using wireless communication infrastructure. Current O-RAN specifications lack the architectural primitives for sensing integration: no service models expose physical-layer observables, no execution frameworks support sub-millisecond sensing tasks, and fronthaul interfaces cannot correlate transmitted waveforms with their reflections. This article proposes three extensions to O-RAN for monostatic sensing, where transmission and reception are co-located at the base station. First, we specify sensing dApps at the O-DU that process IQ samples to extract delay, Doppler, and angular features. Second, we define E2SM-SENS, a service model enabling xApps to subscribe to sensing telemetry with configurable periodicity. Third, we identify required Open Fronthaul metadata for waveform-echo association. We validate the architecture through a prototype implementation using beamforming and Full-Duplex operation, demonstrating closed-loop control with median end-to-end latency suitable for near-real-time sensing applications. While focused on monostatic configurations, the proposed interfaces extend to bistatic and cooperative sensing scenarios.
mm-NOLOC: mmWave-based Localization for Mobile Networks without 3GPP Location Service
Zenodo (CERN European Organization for Nuclear Research) · 2025-10-23
otherOpen accessAccurate localization in dense urban areas remains a significant challenge due to the limitations of Global Navigation Satellite Systems (GNSS) in environments with obstacles and reflections, such as urban canyons. While the most recent 3GPP standards offer sophisticated network-centric positioning techniques, their widespread deployment will take time and is hindered by high infrastructure costs and complexity. In this work, we present mm-NOLOC, a UE-centric localization system, designed as a practical fallback when GNSS fails to deliver high accuracy, that leverages the growing deployment of 5G mmWave infrastructure in dense urban areas. Unlike traditional approaches, mm-NOLOC operates independently of 3GPP location support and utilizes only standardized control-plane information collected solely on the UE side – Synchronization Signal Block (SSB) Indices that are mapped to 5G mmWave beam directions – to obtain robust position estimations. To address the uncertainty introduced by urban multipath, mm-NOLOC models the SSB-to-angle relationship as a discrete and multimodal distribution, based on empirical measurements in operational 5G mmWave networks, and uses a particle filter to refine position estimates by integrating probabilistic observations with UE-side motion dynamics. We validate mm-NOLOC through experiments over commercial 5G mmWave deployments, as well as trace-based simulations. Our results show that mm-NOLOC achieves a median localization error below 3 m and a 95th percentile error below 10 m, offering a practical fallback localization solution in urban canyon scenarios for 5G networks without network location support.
Recent grants
CAREER: A Millimeter-Wave Multi-Layer WLAN Architecture for Multi-Gigabit, Always-On Connectivity
NSF · $123k · 2021–2023
NeTS: Medium: Collaborative Research: Scaling WLANs in Spectrum, User Density, and Robustness
NSF · $540k · 2018–2021
II-New: X60: A Cross-Layer Reconfigurable Multi-Gigabit WLAN Testbed at 60 GHz
NSF · $630k · 2016–2018
CAREER: A Millimeter-Wave Multi-Layer WLAN Architecture for Multi-Gigabit, Always-On Connectivity
NSF · $563k · 2016–2021
NSF · $2.1M · 2021–2026
Frequent coauthors
- 26 shared
Aaron Striegel
University of Notre Dame
- 25 shared
Ethiopia Ngussie
Rutgers Sexual and Reproductive Health and Rights
- 25 shared
Habtamu Abie
Hong Kong Polytechnic University
- 25 shared
Lei Xie
University of Electronic Science and Technology of China
- 25 shared
Yun Lin
Rutgers Sexual and Reproductive Health and Rights
- 25 shared
Alhussein A. Abouzeid
Rensselaer Polytechnic Institute
- 25 shared
Yingying Chen
South China Agricultural University
- 25 shared
Mingyue Ji
Sapienza University of Rome
Labs
WiNS LabPI
Awards & honors
- IEEE Region 1 Technological Innovation (Academic) Award (201…
- UB Teaching Innovation Award (2018)
- NSF CAREER Award (2016)
- UB School of Engineering and Applied Sciences Senior Teacher…
- Early Career Researcher of the Year Award (2015)
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