arXiv subjects

Ivan Seskar

Publications and source records attributed to Ivan Seskar.

At least 19 recordsLinked to original sources

arXiv2026

Modeling and Mitigation of 7.125-7.40 GHz Terrestrial Network RFI on the Passive Earth Exploration Satellite Service in 6.725-7.125 GHz Band

The 7.125-7.4 GHz band is attractive for next generation Terrestrial Network (TN) deployments owing to the large bandwidths available and favorable propagation characteristics. Furthermore, recent U.S. Presidential actions have cleared the usage of this band for 6G by stipulating relocation of federal incumbents that share this band. However, this deployment can only be successful if we can also guarantee coexistence of these networks with existing incumbents operating in adjacent bands. This paper presents a comprehensive analysis of the Radio Frequency Interference (RFI) caused by the proposed TNs in the 7.125-7.4 GHz band at passive Earth Exploration Satellite Service (EESS) sensors that operate in the adjacent 6.725-7.125 GHz band. Using TN base stations (BSs) equipped with filtennas (filtering antennas) as well as transmit precoders for RFI mitigation, we carry out an RFI analysis that accounts for increasing BS deployments in the contiguous U.S. over a 10 year period from 2030 to 2040. We also characterize the size of the guard bands needed to protect the EESS sensors for different BS deployment densities. With appropriate filtenna and precoder design, our results reveal that a 100 Mbps increase in the rate requirements of the TN users results in an RFI increase of roughly 2.45 dB at the EESS sensors. For a 25 MHz Guard Band, simulations show that in 2030, there is no significant RFI for user rates upto 500 Mbps. However, the same systems in 2040 would cause RFI that is around 4 dB above the ITU mandated threshold for passive EESS sensors. This would need to be countered by (a) increasing Guard Band width to 35 MHz, or (b) by reducing the user data rate requirements to 300 Mbps.

eess.SP↗

arXiv2026

Energy Efficiency Testing and Modeling of a Commercial O-RAN System

Network energy efficiency is of critical importance to mobile network operators for economic and ecological reasons. The advent of the O-RAN architecture has brought disaggregation and virtualization, and in order to achieve the highest energy savings gains, we need rigorous measurement, analysis, and modeling of energy consumption at both the component and system levels. However, there remains a lack of publicly-available, quantitative data characterizing the behavior of commercial-grade O-RAN systems. In this white paper, we present a detailed energy-efficiency characterization and modeling of a commercial O-RAN system based on comprehensive power and performance measurements, using a network deployment that faithfully replicates a production O-RAN network deployed by a wireless carrier. The results are drawn from an energy test campaign conducted through a joint collaboration between the Open RAN Center for Integration and Deployment (ORCID) Lab Testing and Evaluation (T&E) Project and the Open Networking Foundation / Rutgers WINLAB Energy Efficiency R&D project. The test environment includes an O-RAN system with an AWS-hosted O-CU, a dedicated-server O-DU, and six high-power, multi-band O-RUs. Our results identify the dominant factors influencing power consumption across the O-RAN stack and quantify energy usage variation under different operational and traffic scenarios. These measurements can be used by operators to parameterize power-consumption models, ultimately supporting data-driven energy optimization and more sustainable operation of commercial O-RAN networks.

cs.NI↗

arXiv2025

Over-the-Air Transmission of Zak-OTFS on mmWave Communications Testbed

Millimeter-wave (mmWave) communication offers vast bandwidth for next-generation wireless systems but faces severe path loss, Doppler effects, and hardware impairments. Orthogonal Time Frequency Space (OTFS) modulation has emerged as a robust waveform for high-mobility and doubly dispersive channels, outperforming OFDM under strong Doppler. However, the most studied multicarrier OTFS (MC-OTFS) is not easily predictable because the input-output (I$/$O) relation is not given by (twisted) convolution. Recently, the Zak-transform based OTFS (Zak-OTFS or OTFS 2$.$0) was proposed, which provides a single domain delay Doppler (DD) processing framework with predictable I$/$O behavior. This paper presents one of the first over-the-air (OTA) demonstrations of Zak-OTFS at mmWave frequencies. We design a complete Zak-OTFS based mmWave OTA system featuring root-raised-cosine (RRC) filtering for enhanced DD-domain predictability, higher-order modulations up to 16-QAM, and a low-overhead preamble for synchronization. A comprehensive signal model incorporating carrier frequency offset (CFO) and timing impairments is developed, showing these effects can be jointly captured within the effective DD-domain channel. Experimental validation on the COSMOS testbed confirms the feasibility and robustness of Zak-OTFS under realistic mmWave conditions, highlighting its potential for efficient implementations in beyond-5G and 6G systems.

eess.SP↗

arXiv2024

Timely and Energy-Efficient Multi-Step Update Processing

This work explores systems where source updates require multiple sequential processing steps. We model and analyze the Age of Information (AoI) performance of various system designs under both parallel and series server setups. In parallel setups, each processor executes all computation steps with multiple processors working in parallel, while in series setups, each processor performs a specific step in sequence. In practice, processing faster is better in terms of age but it also consumes more power. We identify the occurrence of wasted power in these setups, which arises when processing efforts do not lead to a reduction in age. This happens when a fresher update finishes first in parallel servers or when a server preempts processing due to a fresher update from preceding server in series setups. To address this age-power trade-off, we formulate and solve an optimization problem to determine the optimal service rates for each processing step under a given power budget. We focus on a special case where updates require two computational steps.

cs.IT↗

arXiv2024

Wall-Street: An Intelligent Vehicular Surface for Reliable mmWave Handover

mmWave networks promise high bandwidth but face significant challenges in maintaining reliable connections for users moving at high speed. Frequent handovers, complex beam alignment, and signal blockage from car bodies lead to service interruptions and degraded performance. We present Wall-Street, a vehicle-mounted smart surface that enhances mmWave connectivity for in-vehicle users. Wall-Street improves mobility management by (1) steering outdoor mmWave signals into the vehicle for shared coverage and providing a single, collective handover for all users; (2) performing neighbor-cell search without interrupting data transfer, ensuring seamless handovers; and (3) connecting users to a new cell before disconnecting from the old cell for reliable cell transitions. We implemented and integrated Wall-Street into the COSMOS testbed. We collected PHY traces with multiple base station nodes and in-vehicle user nodes with a surface-mounted vehicle, driving on a nearby road. Our trace-driven ns-3 simulation demonstrates a throughput im- provement of up to 78% and a latency reduction of up to 34% over the standard Standalone handover scheme.

cs.NI↗

arXiv2024

Efficient and Timely Memory Access

This paper investigates the optimization of memory sampling in status updating systems, where source updates are published in shared memory, and reader process samples the memory for source updates by paying a sampling cost. We formulate a discrete-time decision problem to find a sampling policy that minimizes average cost comprising age at the client and the cost incurred due to sampling. We establish that an optimal policy is a stationary and deterministic threshold-type policy, and subsequently derive optimal threshold and the corresponding optimal average cost.

eess.SY↗

arXiv2024

Decentralized Multi-Party Multi-Network AI for Global Deployment of 6G Wireless Systems

Multiple visions of 6G networks elicit Artificial Intelligence (AI) as a central, native element. When 6G systems are deployed at a large scale, end-to-end AI-based solutions will necessarily have to encompass both the radio and the fiber-optical domain. This paper introduces the Decentralized Multi-Party, Multi-Network AI (DMMAI) framework for integrating AI into 6G networks deployed at scale. DMMAI harmonizes AI-driven controls across diverse network platforms and thus facilitates networks that autonomously configure, monitor, and repair themselves. This is particularly crucial at the network edge, where advanced applications meet heightened functionality and security demands. The radio/optical integration is vital due to the current compartmentalization of AI research within these domains, which lacks a comprehensive understanding of their interaction. Our approach explores multi-network orchestration and AI control integration, filling a critical gap in standardized frameworks for AI-driven coordination in 6G networks. The DMMAI framework is a step towards a global standard for AI in 6G, aiming to establish reference use cases, data and model management methods, and benchmarking platforms for future AI/ML solutions.

cs.NI↗

arXiv2024

Design and Testbed Deployment of Frequency-Domain Equalization Full Duplex Radios

Full-duplex (FD) wireless can significantly enhance spectrum efficiency but requires effective self-interference (SI) cancellers. RF SI cancellation (SIC) via frequency-domain equalization (FDE), where bandpass filters channelize the SI, is suited for integrated circuits (ICs). In this paper, we explore the limits and higher layer challenges associated with using such cancellers. We evaluate the performance of a custom FDE-based canceller using two testbeds; one with mobile FD radios and the other with upgraded, static FD radios in the PAWR COSMOS testbed. The latter is a lasting artifact for the research community, alongside a dataset containing baseband waveforms captured on the COSMOS FD radios, facilitating FD-related experimentation at the higher networking layers. We evaluate the performance of the FDE-based FD radios in both testbeds, with experiments showing 95 dB overall achieved SIC (52 dB from RF SIC) across 20 MHz bandwidth, and an average link-level FD rate gain of 1.87x. We also conduct experiments in (i) uplink-downlink networks with inter-user interference, and (ii) heterogeneous networks with half-duplex and FD users. The experimental FD gains in the two types of networks depend on the users' SNR values and the number of FD users, and are 1.14x-1.25x and 1.25x-1.73x, respectively, confirming previous analytical results.

cs.NI↗

arXiv2023

High-speed sensing of RF signals with phase change materials

RF radiation spectrum is central to wireless and radar systems among numerous high-frequency device technologies. Here, we demonstrate sensing of RF signals in the technologically relevant 2.4 GHz range utilizing vanadium dioxide (VO2), a quantum material that has garnered significant interest for its insulator-to-metal transition. We find the electrical resistance of both stoichiometric as well as off-stoichiometric vanadium oxide films can be modulated with RF wave exposures from a distance. The response of the materials to the RF waves can be enhanced by either increasing the power received by the sample or reducing channel separation. We report a significant ~73% drop in resistance with a 5 {\mu}m channel gap of the VO2 film at a characteristic response time of 16 microseconds. The peak sensitivity is proximal to the phase transition temperature boundary that can be engineered via doping and crystal chemistry. Dynamic sensing measurements highlight the films' rapid response and broad-spectrum sensitivity. Engineering electronic phase boundaries in correlated electron systems could offer new capabilities in emerging communication technologies.

physics.app-ph↗

arXiv2023

MEC-Intelligent Agent Support for Low-Latency Data Plane in Private NextG Core

Private 5G networks will soon be ubiquitous across the future-generation smart wireless access infrastructures hosting a wide range of performance-critical applications. A high-performing User Plane Function (UPF) in the data plane is critical to achieving such stringent performance goals, as it governs fast packet processing and supports several key control-plane operations. Based on a private 5G prototype implementation and analysis, it is imperative to perform dynamic resource management and orchestration at the UPF. This paper leverages Mobile Edge Cloud-Intelligent Agent (MEC-IA), a logically centralized entity that proactively distributes resources at UPF for various service types, significantly reducing the tail latency experienced by the user requests while maximizing resource utilization. Extending the MEC-IA functionality to MEC layers further incurs data plane latency reduction. Based on our extensive simulations, under skewed uRLLC traffic arrival, the MEC-IA assisted bestfit UPF-MEC scheme reduces the worst-case latency of UE requests by up to 77.8% w.r.t. baseline. Additionally, the system can increase uRLLC connectivity gain by 2.40x while obtaining 40% CapEx savings.

cs.NI↗

arXiv2023

Timely Processing Of Updates From Multiple Sources

We consider a system where the updates from independent sources are disseminated via a publish-subscribe mechanism. The sources are the publishers and a decision process (DP), acting as a subscriber, derives decision updates from the source data. We derive the stationary expected age of information (AoI) of decision updates delivered to a monitor. We show that a lazy computation policy in which the DP may sit idle before computing its next decision update can reduce the average AoI at the monitor even though the DP exerts no control over the generation of source updates. This AoI reduction is shown to occur because lazy computation can offset the negative effect of high variance in the computation time.

cs.IT↗

arXiv2022

Channel Estimation for Massive MIMO systems using Tensor Cores in GPU

For efficient use of Massive MIMO systems, fast and accurate channel estimation is very important. But the Large-scale antenna array presence requires high pilot overhead for high accuracy of estimation. Also, when used with software-based processing systems like CPUs and GPUs, high processing latency becomes a major issue. To reduce Pilot overhead, a Pilot transmission scheme in combination with PN Sequence correlation based channel estimation scheme is implemented. Then, to deal with the issue of high processing latency, Tensor Cores in Nvidia GPUs are used for computing the channel estimation. Experiments are performed by using Nvidia V100 GPU in the ORBIT Testbed to show the performance of the Pilot transmission scheme. By varying factors like PN sequence length, Channel Impulse Response length, number of multiplexed transmitters, and scale of MIMO, the accuracy and processing latency of Tensor Core implementation of the Channel Estimation is evaluated.

cs.DC↗

arXiv2022

Smart City Intersections: Intelligence Nodes for Future Metropolises

Traffic intersections are the most suitable locations for the deployment of computing, communications, and intelligence services for smart cities of the future. The abundance of data to be collected and processed, in combination with privacy and security concerns, motivates the use of the edge-computing paradigm which aligns well with physical intersections in metropolises. This paper focuses on high-bandwidth, low-latency applications, and in that context it describes: (i) system design considerations for smart city intersection intelligence nodes; (ii) key technological components including sensors, networking, edge computing, low latency design, and AI-based intelligence; and (iii) applications such as privacy preservation, cloud-connected vehicles, a real-time "radar-screen", traffic management, and monitoring of pedestrian behavior during pandemics. The results of the experimental studies performed on the COSMOS testbed located in New York City are illustrated. Future challenges in designing human-centered smart city intersections are summarized.

cs.CV↗

arXiv2022

Implementation of FGPA based Channel Sounder for Large scale antenna systems using RFNoC on USRP Platform

This paper concentrates on building a multi-antenna FPGA based Channel Sounder with single transmitter and multiple receivers to realize wireless propagation characteristics of an indoor environment. A DSSS signal (spread with a real maximum length PN sequence) is transmitted, which is correlated with the same PN sequence at each receiver to obtain the power delay profile . Multiple power delay profiles are averaged and the result is then sent to host. To utilize high bandwidth, the computationally expensive tasks related to generation and parallel correlation of PN sequences are moved to the FPGA present in each USRP (Universal Software Radio Peripheral). Channel sounder blocks were built using Vivado HLS and integrated with RFNoC (RF Network on Chip) framework, which were then used on USRP X310 devices.

eess.SP↗

arXiv2022

Distributed Processing for Encoding and Decoding of Binary LDPC codes using MPI

Low Density Parity Check (LDPC) codes are linear error correcting codes used in communication systems for Forward Error Correction (FEC). But, intensive computation is required for encoding and decoding of LDPC codes, making it difficult for practical usage in general purpose software based signal processing systems. In order to accelerate the encoding and decoding of LDPC codes, distributed processing over multiple multi-core CPUs using Message Passing Interface (MPI) is performed. Implementation is done using Stream Processing and Batch Processing mechanisms and the execution time for both implementations is compared w.r.t variation in number of CPUs and number of cores per CPU. Performance evaluation of distributed processing is shown by variation in execution time w.r.t. increase in number of processors (CPU cores).

cs.DC↗

arXiv2019

Accelerating Channel Estimation and Demodulation of Uplink OFDM symbols for Large Scale Antenna Systems using GPU

Increase in the number of antennas in the front-end increases the volume of data to be processed at the back-end. This establishes a need for acceleration in back-end processing. To solve the issue of high volume data processing at back-end, a GPU is utilized. Acceleration for Least Squares channel estimation and demodulation of uplink OFDM symbols is provided by using a combination of CPU and GPU at the back-end. Single user uplink scenario is implemented in near real-time manner using the USRP platform present in the Large scale antenna systems in ORBIT Testbed. The number of antennas and FFT length are varied to provide different scenarios for comparison. The performance of both CPU and GPU is compared for each process.

cs.DC↗

arXiv2018

The Future of CISE Distributed Research Infrastructure

Shared research infrastructure that is globally distributed and widely accessible has been a hallmark of the networking community. This paper presents an initial snapshot of a vision for a possible future of mid-scale distributed research infrastructure aimed at enabling new types of research and discoveries. The paper is written from the perspective of "lessons learned" in constructing and operating the Global Environment for Network Innovations (GENI) infrastructure and attempts to project future concepts and solutions based on these lessons. The goal of this paper is to engage the community to contribute new ideas and to inform funding agencies about future research directions to realize this vision.

cs.NI↗

arXiv2017

Demo Abstract: CDMA-based IoT Services with Shared Band Operation of LTE in 5G

With the vision of deployment of massive Internet-of-Things (IoTs) in 5G network, existing 4G network and protocols are inefficient to handle sporadic IoT traffic with requirements of low-latency, low control overhead and low power. To suffice these requirements, we propose a design of a PHY/MAC layer using Software Defined Radios (SDRs) that is backward compatible with existing OFDM based LTE protocols and supports CDMA based transmissions for low power IoT devices as well. This demo shows our implemented system based on that design and the viability of the proposal under different network scenarios.

cs.NI↗