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Marco Mezzavilla

Publications and source records attributed to Marco Mezzavilla.

At least 37 records · Page 2Linked to original sources

Terrestrial-Satellite Spectrum Sharing in the Upper Mid-Band with Interference Nulling

The growing demand for broader bandwidth in cellular networks has turned the upper mid-band (7-24 GHz) into a focal point for expansion. However, the integration of terrestrial cellular and incumbent satellite services, particularly in the 12 GHz band, poses significant interference challenges. This paper investigates the interference dynamics in terrestrial-satellite coexistence scenarios and introduces a novel beamforming approach that leverages available ephemeris data for dynamic interference mitigation. By establishing spatial radiation nulls directed towards visible satellites, our technique ensures the protection of satellite uplink communications without markedly compromising terrestrial downlink quality. Through a practical case study, we demonstrate that our approach maintains the satellite uplink signal-to-noise ratio (SNR) degradation under 0.1 dB and incurs only a negligible SNR penalty for the terrestrial downlink. Our findings offer a promising pathway for efficient spectrum sharing in the upper mid-band, fostering a concurrent enhancement in both terrestrial and satellite network capacity.

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Cellular Wireless Networks in the Upper Mid-Band

The upper mid-band - roughly from 7 to 24 GHz - has attracted considerable recent interest for new cellular services. This frequency range has vastly more spectrum than the highly congested bands below 7 GHz while offering more favorable propagation and coverage than the millimeter wave (mmWave) frequencies. The upper mid-band can thus provide a powerful and complementary frequency range to balance coverage and capacity. Realizing the full potential of these bands, however, will require fundamental changes to the design of cellular systems. Most importantly, spectrum will likely need to be shared with incumbents including communication satellites, military RADAR, and radio astronomy. Also, the upper mid-band is simply a vast frequency range. Due to this wide bandwidth, combined with the directional nature of transmission and intermittent occupancy of incumbents, cellular systems will need to be agile to sense and intelligently use large spatial and frequency degrees of freedom. This paper attempts to provide an initial assessment of the feasibility and potential gains of wideband cellular systems operating in the upper mid-band. The study includes: (1) a system study to assess potential gains of multi-band systems in a representative dense urban environment and illustrate the value of wide band system with dynamic frequency selectivity; (2) an evaluation of potential cross interference between satellites and terrestrial cellular services and interference nulling to reduce that interference; and (3) design and evaluation of a compact multi-band antenna array structure. Leveraging these preliminary results, we identify potential future research directions to realize next-generation systems in these frequencies.

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5G Edge Vision: Wearable Assistive Technology for People with Blindness and Low Vision

In an increasingly visual world, people with blindness and low vision (pBLV) face substantial challenges in navigating their surroundings and interpreting visual information. From our previous work, VIS4ION is a smart wearable that helps pBLV in their day-to-day challenges. It enables multiple artificial intelligence (AI)-based microservices such as visual scene processing, navigation, and vision-language inference. These microservices require powerful computational resources and, in some cases, stringent inference times, hence the need to offload computation to edge servers. This paper introduces a novel video streaming platform that improves the capabilities of VIS4ION by providing real-time support of the microservices at the network edge. When video is offloaded wirelessly to the edge, the time-varying nature of the wireless network requires the use of adaptation strategies for a seamless video service. We demonstrate the performance of an adaptive real-time video streaming platform through experimentation with an open-source 5G deployment based on open air interface (OAI). The experiments demonstrate the ability to provide the microservices robustly in time-varying network loads.

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An Experimental Prototype for Multistatic Asynchronous ISAC

We prototype and validate a multistatic mmWave ISAC system based on IEEE802.11ay. Compensation of the clock asynchrony between each TX and RX pair is performed using the sole LoS wireless signal propagation. As a result, our system provides concurrent target tracking and micro-Doppler estimation from multiple points of view, paving the way for practical multistatic data fusion. Our results on human movement sensing, complemented with precise, quantitative GT data, demonstrate the enhanced sensing capabilities of multistatic ISAC, due to the spatial diversity of the receiver nodes.

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Parametrization and Estimation of High-Rank Line-of-Sight MIMO Channels with Reflected Paths

High-rank line-of-sight (LOS) MIMO systems have attracted considerable attention for millimeter wave and THz communications. The small wavelengths in these frequencies enable spatial multiplexing with massive data rates at long distances. Such systems are also being considered for multi-path non-LOS (NLOS) environments. In these scenarios, standard channel models based on plane waves cannot capture the curvature of each wave front necessary to model spatial multiplexing. This work presents a novel and simple multi-path wireless channel parametrization where each path is replaced by a LOS path with a reflected image source. The model fully is valid for all paths with specular planar reflections and captures the spherical nature of each wave front. Importantly, it is shown that the model uses only two additional parameters relative to the standard plane wave model. Moreover, the parameters can be easily captured in standard ray tracing. The accuracy of the approach is demonstrated on detailed ray tracing simulations at 28 GHz and 140 GHz in a dense urban area.

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Multi-Frequency Channel Modeling for Millimeter Wave and THz Wireless Communication via Generative Adversarial Networks

Modern cellular systems rely increasingly on simultaneous communication in multiple discontinuous bands for macro-diversity and increased bandwidth. Multi-frequency communication is particularly crucial in the millimeter wave (mmWave) and Terahertz (THz) frequencies, as these bands are often coupled with lower frequencies for robustness. Evaluation of these systems requires statistical models that can capture the joint distribution of the channel paths across multiple frequencies. This paper presents a general neural network based methodology for training multi-frequency double directional statistical channel models. In the proposed approach, each is described as a multi-clustered set, and a generative adversarial network (GAN) is trained to generate random multi-cluster profiles where the generated cluster data includes the angles and delay of the clusters along with the vectors of random received powers, angular, and delay spread at different frequencies. The model can be readily applied for multi-frequency link or network layer simulation. The methodology is demonstrated on modeling urban micro-cellular links at 28 and 140 GHz trained from extensive ray tracing data. The methodology makes minimal statistical assumptions and experiments show the model can capture interesting statistical relationships between frequencies.

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Coexistence of UAVs and Terrestrial Users in Millimeter-Wave Urban Networks

5G millimeter-wave (mmWave) cellular networks are in the early phase of commercial deployments and present a unique opportunity for robust, high-data-rate communication to unmanned aerial vehicles (UAVs). A fundamental question is whether and how mmWave networks designed for terrestrial users should be modified to serve UAVs. The paper invokes realistic cell layouts, antenna patterns, and channel models trained from extensive ray tracing data to assess the performance of various network alternatives. Importantly, the study considers the addition of dedicated uptilted rooftop-mounted cells for aerial coverage, as well as novel spectrum sharing modes between terrestrial and aerial network operators. The effect of power control and of multiuser multiple-input multiple-output are also studied.

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Wireless Channel Prediction in Partially Observed Environments

Site-specific radio frequency (RF) propagation prediction increasingly relies on models built from visual data such as cameras and LIDAR sensors. When operating in dynamic settings, the environment may only be partially observed. This paper introduces a method to extract statistical channel models, given partial observations of the surrounding environment. We propose a simple heuristic algorithm that performs ray tracing on the partial environment and then uses machine-learning trained predictors to estimate the channel and its uncertainty from features extracted from the partial ray tracing results. It is shown that the proposed method can interpolate between fully statistical models when no partial information is available and fully deterministic models when the environment is completely observed. The method can also capture the degree of uncertainty of the propagation predictions depending on the amount of region that has been explored. The methodology is demonstrated in a robotic navigation application simulated on a set of indoor maps with detailed models constructed using state-of-the-art navigation, simultaneous localization and mapping (SLAM), and computer vision methods.

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Network-Aware 5G Edge Computing for Object Detection: Augmenting Wearables to "See" More, Farther and Faster

Advanced wearable devices are increasingly incorporating high-resolution multi-camera systems. As state-of-the-art neural networks for processing the resulting image data are computationally demanding, there has been growing interest in leveraging fifth generation (5G) wireless connectivity and mobile edge computing for offloading this processing to the cloud. To assess this possibility, this paper presents a detailed simulation and evaluation of 5G wireless offloading for object detection within a powerful, new smart wearable called VIS4ION, for the Blind-and-Visually Impaired (BVI). The current VIS4ION system is an instrumented book-bag with high-resolution cameras, vision processing and haptic and audio feedback. The paper considers uploading the camera data to a mobile edge cloud to perform real-time object detection and transmitting the detection results back to the wearable. To determine the video requirements, the paper evaluates the impact of video bit rate and resolution on object detection accuracy and range. A new street scene dataset with labeled objects relevant to BVI navigation is leveraged for analysis. The vision evaluation is combined with a detailed full-stack wireless network simulation to determine the distribution of throughputs and delays with real navigation paths and ray-tracing from new high-resolution 3D models in an urban environment. For comparison, the wireless simulation considers both a standard 4G-Long Term Evolution (LTE) carrier and high-rate 5G millimeter-wave (mmWave) carrier. The work thus provides a thorough and realistic assessment of edge computing with mmWave connectivity in an application with both high bandwidth and low latency requirements.

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Understanding Energy Efficiency and Interference Tolerance in Millimeter Wave Receivers

Power consumption is a key challenge in millimeter wave (mmWave) receiver front-ends, due to the need to support high dimensional antenna arrays at wide bandwidths. Recently, there has been considerable work in developing low-power front-ends, often based on low-resolution ADCs and low-power mixers. A critical but less studied consequence of such designs is the relatively low-dynamic range which in turn exposes the receiver to adjacent carrier interference and blockers. This paper provides a general mathematical framework for analyzing the performance of mmWave front-ends in the presence of out-of-band interference. The goal is to elucidate the fundamental trade-off of power consumption, interference tolerance and in-band performance. The analysis is combined with detailed network simulations in cellular systems with multiple carriers, as well as detailed circuit simulations of key components at 140 GHz. The analysis reveals critical bottlenecks for low-power interference robustness and suggests designs enhancements for use in practical systems.

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Millimeter-Wave UAV Coverage in Urban Environments

With growing interest in mmWave connectivity for UAVs, a basic question is whether networks intended for terrestrial users can provide sufficient aerial coverage as well. To assess this possibility, the paper proposes a novel evaluation methodology using generative models trained on detailed ray tracing data. These models capture complex propagation characteristics and can be readily combined with antenna and beamforming assumptions. Extensive simulation using these models indicate that standard (street-level and downtilted) base stations at typical microcellular densities can indeed provide satisfactory UAV coverage. Interestingly, the coverage is possible via a conjunction of antenna sidelobes and strong reflections. With sparser deployments, the coverage is only guaranteed at progressively higher altitudes. Additional dedicated (rooftop-mounted and uptilted) base stations strengthen the coverage provided that their density is comparable to that of the standard deployment, and would be instrumental for sparse deployments of the latter.

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What Will the Future of UAV Cellular Communications Be? A Flight from 5G to 6G

What will the future of UAV cellular communications be? In this tutorial article, we address such a compelling yet difficult question by embarking on a journey from 5G to 6G and sharing a large number of realistic case studies supported by original results. We start by overviewing the status quo on UAV communications from an industrial standpoint, providing fresh updates from the 3GPP and detailing new 5G NR features in support of aerial devices. We then show the potential and the limitations of such features. In particular, we demonstrate how sub-6 GHz massive MIMO can successfully tackle cell selection and interference challenges, we showcase encouraging mmWave coverage evaluations in both urban and suburban/rural settings, and we examine the peculiarities of direct device-to-device communications in the sky. Moving on, we sneak a peek at next-generation UAV communications, listing some of the use cases envisioned for the 2030s. We identify the most promising 6G enablers for UAV communication, those expected to take the performance and reliability to the next level. For each of these disruptive new paradigms (non-terrestrial networks, cell-free architectures, artificial intelligence, reconfigurable intelligent surfaces, and THz communications), we gauge the prospective benefits for UAVs and discuss the main technological hurdles that stand in the way. All along, we distil our numerous findings into essential takeaways, and we identify key open problems worthy of further study.

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Lightweight UAV-based Measurement System for Air-to-Ground Channels at 28 GHz

Wireless communication at millimeter wave frequencies has attracted considerable attention for the delivery of high-bit-rate connectivity to unmanned aerial vehicles (UAVs). However, conducting the channel measurements necessary to assess communication at these frequencies has been challenging due to the severe payload and power restrictions in commercial UAVs. This work presents a novel lightweight (approximately 1.3 kg) channel measurement system at 28 GHz installed on a commercially available UAV. A ground transmitter equipped with a horn antenna conveys sounding signals to a UAV equipped with a lightweight spectrum analyzer. We demonstrate that the measurements can be highly influenced by the antenna pattern as shaped by the UAV's frame. A calibration procedure is presented to correct for the resulting angular variations in antenna gain. The measurement setup is then validated on real flights from an airstrip at distances in excess of 300 m.

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Millimeter Wave Channel Modeling via Generative Neural Networks

Statistical channel models are instrumental to design and evaluate wireless communication systems. In the millimeter wave bands, such models become acutely challenging; they must capture the delay, directions, and path gains, for each link and with high resolution. This paper presents a general modeling methodology based on training generative neural networks from data. The proposed generative model consists of a two-stage structure that first predicts the state of each link (line-of-sight, non-line-of-sight, or outage), and subsequently feeds this state into a conditional variational autoencoder that generates the path losses, delays, and angles of arrival and departure for all its propagation paths. Importantly, minimal prior assumptions are made, enabling the model to capture complex relationships within the data. The methodology is demonstrated for 28GHz air-to-ground channels in an urban environment, with training datasets produced by means of ray tracing.

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Enabling Remote Whole-Body Control with 5G Edge Computing

Real-world applications require light-weight, energy-efficient, fully autonomous robots. Yet, increasing autonomy is oftentimes synonymous with escalating computational requirements. It might thus be desirable to offload intensive computation--not only sensing and planning, but also low-level whole-body control--to remote servers in order to reduce on-board computational needs. Fifth Generation (5G) wireless cellular technology, with its low latency and high bandwidth capabilities, has the potential to unlock cloud-based high performance control of complex robots. However, state-of-the-art control algorithms for legged robots can only tolerate very low control delays, which even ultra-low latency 5G edge computing can sometimes fail to achieve. In this work, we investigate the problem of cloud-based whole-body control of legged robots over a 5G link. We propose a novel approach that consists of a standard optimization-based controller on the network edge and a local linear, approximately optimal controller that significantly reduces on-board computational needs while increasing robustness to delay and possible loss of communication. Simulation experiments on humanoid balancing and walking tasks that includes a realistic 5G communication model demonstrate significant improvement of the reliability of robot locomotion under jitter and delays likely to experienced in 5G wireless links.

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Xilinx RF-SoC-based Digital Multi-Beam Array Processors for 28/60~GHz Wireless Testbeds

Emerging wireless applications such as 5G cellular, large intelligent surfaces (LIS), and holographic massive MIMO require antenna array processing at mm-wave frequencies with large numbers of independent digital transceivers. This paper summarizes the authors' recent progress on the design and testing of 28 GHz and 60 GHz fully-digital array processing platforms based on wideband reconfigurable FPGA-based software-defined radios (SDRs). The digital baseband and microwave interfacing aspects of the SDRs are implemented on single-chip RF system-on-chip (RF-SoC) processors from Xilinx. Two versions of the RF-SoC technology (ZCU-111 and ZCU-1275) were used to implement fully-digital real-time array processors at 28~GHz (realizing 4 parallel beams with 0.8 GHz bandwidth per beam) and 60~GHz (realizing 4 parallel beams with 1.8~GHz bandwidth per beam). Dielectric lenslet arrays fed by a digital phased-array feed (PAF) located on the focal plane are proposed for further increasing antenna array gain.

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Millimeter Wave Remove UAV Control and Communications for Public Safety Scenarios

Communication and video capture from unmanned aerial vehicles (UAVs) offer significant potential for assisting first responders in remote public safety settings. In such uses, millimeter wave (mmWave) wireless links can provide high throughput and low latency connectivity between the UAV and a remote command center. However, maintaining reliable aerial communication in the mmWave bands is challenging due to the need to support high speed beam tracking and overcome blockage. This paper provides a simulation study aimed at assessing the feasibility of public safety UAV connectivity through a 5G link at 28 GHz. Real flight motion traces are captured during maneuvers similar to those expected in public safety settings. The motions traces are then incorporated into a detailed mmWave network simulator that models the channel, blockage, beamforming and full 3GPP protocol stack. We show that 5G mmWave communications can deliver throughput up to 1 Gbps with consistent sub ms latency when the base station is located near the mission area, enabling remote offloading of the UAV control and perception algorithms.

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Towards 6G Networks: Use Cases and Technologies

Reliable data connectivity is vital for the ever increasingly intelligent, automated and ubiquitous digital world. Mobile networks are the data highways and, in a fully connected, intelligent digital world, will need to connect everything, from people to vehicles, sensors, data, cloud resources and even robotic agents. Fifth generation (5G) wireless networks (that are being currently deployed) offer significant advances beyond LTE, but may be unable to meet the full connectivity demands of the future digital society. Therefore, this article discusses technologies that will evolve wireless networks towards a sixth generation (6G), and that we consider as enablers for several potential 6G use cases. We provide a full-stack, system-level perspective on 6G scenarios and requirements, and select 6G technologies that can satisfy them either by improving the 5G design, or by introducing completely new communication paradigms.

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