arXiv subjects

Matteo Pagin

Publications and source records attributed to Matteo Pagin.

15 recordsLinked to original sources

arXiv2026

End-to-End Simulation of 5G NR Integrated Access and Backhaul Networks for Remote Maritime Connectivity

Millimeter wave (mmWave) 5th generation (5G) networks offer high data rates but face coverage challenges due to severe path loss and blockage. These problems motivate the use of Integrated Access and Backhaul (IAB) as a flexible wireless backhaul solution that extends connectivity to cell boundaries and unfibered areas, including maritime environments. This paper overviews the latest 3GPP specifications for IAB networks in Releases 16 through 18. Then, it presents an ns-3 module for IAB, featuring a complete end-to-end protocol stack, including the backhaul adaptation protocol (BAP) layer, flexible slot and control configurations, and multiplexing schemes based on both time and frequency division. We test the IAB module via extensive system-level simulations in a custom maritime scenario where vessels, equipped with IAB-nodes, can simultaneously act as access points and relays, forming dynamic multi-hop networks that maintain connectivity via wireless backhaul to shore-based stations. We evaluate different topologies and channel conditions, providing insights into the design and deployment of mmWave IAB networks in offshore environments.

cs.NI↗

arXiv2024

Optimizing Energy Efficiency of 5G RedCap Beam Management for Smart Agriculture Applications

Beam management in 5G NR involves the transmission and reception of control signals such as Synchronization Signal Blocks (SSBs), crucial for tasks like initial access and/or channel estimation. However, this procedure consumes energy, which is particularly challenging to handle for battery-constrained nodes such as RedCap devices. Specifically, in this work we study a mid-market Internet of Things (IoT) Smart Agriculture (SmA) deployment where an Unmanned Autonomous Vehicle (UAV) acts as a base station "from the sky" (UAV-gNB) to monitor and control ground User Equipments (UEs) in the field. Then, we formalize a multi-variate optimization problem to determine the optimal beam management design for RedCap SmA devices in order to reduce the energy consumption at the UAV-gNB. Specifically, we jointly optimize the transmission power and the beamwidth at the UAV-gNB. Based on the analysis, we derive the so-called "regions of feasibility," i.e., the upper limit(s) of the beam management parameters for which RedCap Quality of Service (QoS) and energy constraints are met. We study the impact of factors like the total transmission power at the gNB, the Signal-to-Noise Ratio (SNR) threshold for successful packet decoding, the number of UEs in the region, and the misdetection probability. Simulation results demonstrate that there exists an optimal configuration for beam management to promote energy efficiency, which depends on the speed of the UEs, the beamwidth, and other network parameters.

cs.NI↗

arXiv2023

Minimizing Energy Consumption for 5G NR Beam Management for RedCap Devices

In 5G New Radio (NR), beam management entails periodic and continuous transmission and reception of control signals in the form of synchronization signal blocks (SSBs), used to perform initial access and/or channel estimation. However, this procedure demands continuous energy consumption, which is particularly challenging to handle for low-cost, low-complexity, and battery-constrained devices, such as RedCap devices to support mid-market Internet of Things (IoT) use cases. In this context, this work aims at reducing the energy consumption during beam management for RedCap devices, while ensuring that the desired Quality of Service (QoS) requirements are met. To do so, we formalize an optimization problem in an Indoor Factory (InF) scenario to select the best beam management parameters, including the beam update periodicity and the beamwidth, to minimize energy consumption based on users' distribution and their speed. The analysis yields the regions of feasibility, i.e., the upper limit(s) on the beam management parameters for RedCap devices, that we use to provide design guidelines accordingly.

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arXiv2023

SeBaSi system-level Integrated Access and Backhaul simulator for self-backhauling

millimeter wave (mmWave) and sub-terahertz (THz) communications have the potential of increasing mobile network throughput drastically. However, the challenging propagation conditions experienced at mmWave and beyond frequencies can potentially limit the range of the wireless link down to a few meters, compared to up to kilometers for sub-6GHz links. Thus, increasing the density of base station deployments is required to achieve sufficient coverage in the Radio Access Network (RAN). To such end, 3rd Generation Partnership Project (3GPP) introduced wireless backhauled base stations with Integrated Access and Backhaul (IAB), a key technology to achieve dense networks while preventing the need for costly fiber deployments. In this paper, we introduce SeBaSi, a system-level simulator for IAB networks, and demonstrate its functionality by simulating IAB deployments in Manhattan, New York City and Padova. Finally, we show how SeBaSi can represent a useful tool for the performance evaluation of self-backhauled cellular networks, thanks to its high level of network abstraction, coupled with its open and customizable design, which allows users to extend it to support novel technologies such as Reconfigurable Intelligent Surfaces (RISs)

cs.NI↗

arXiv2023

Downlink Clustering-Based Scheduling of IRS-Assisted Communications With Reconfiguration Constraints

Intelligent reflecting surfaces (IRSs) are being widely investigated as a potential low-cost and energy-efficient alternative to active relays for improving coverage in next-generation cellular networks. However, technical constraints in the configuration of IRSs should be taken into account in the design of scheduling solutions and the assessment of their performance. To this end, we examine an IRS-assisted time division multiple access (TDMA) cellular network where the reconfiguration of the IRS incurs a communication cost; thus, we aim at limiting the number of reconfigurations over time. Along these lines, we propose a clustering-based heuristic scheduling scheme that maximizes the cell sum capacity, subject to a fixed number of reconfigurations within a TDMA frame. First, the best configuration of each user equipment (UE), in terms of joint beamforming and optimal IRS configuration, is determined using an iterative algorithm. Then, we propose different clustering techniques to divide the UEs into subsets sharing the same sub-optimal IRS configuration, derived through distance- and capacity-based algorithms. Finally, UEs within the same cluster are scheduled accordingly. We provide extensive numerical results for different propagation scenarios, IRS sizes, and phase shifters quantization constraints, showing the effectiveness of our approach in supporting multi-user IRS systems with practical constraints.

eess.SP↗

arXiv2023

Implementation of a Channel Model for Non-Terrestrial Networks in ns-3

While the 5th generation (5G) of mobile networks has landed in the commercial area, the research community is exploring new functionalities for 6th generation (6G) networks, for example non-terrestrial networks (NTNs) via space/air nodes such as Unmanned Aerial Vehicles (UAVs), High Altitute Platforms (HAPs) or satellites. Specifically, satellite-based communication offers new opportunities for future wireless applications, such as providing connectivity to remote or otherwise unconnected areas, complementing terrestrial networks to reduce connection downtime, as well as increasing traffic efficiency in hot spot areas. In this context, an accurate characterization of the NTN channel is the first step towards proper protocol design. Along these lines, this paper provides an ns-3 implementation of the 3rd Generation Partnership Project (3GPP) channel and antenna models for NTN described in Technical Report 38.811. In particular, we extend the ns-3 code base with new modules to implement the attenuation of the signal in air/space due to atmospheric gases and scintillation, and new mobility and fading models to account for the Geocentric Cartesian coordinate system of satellites. Finally, we validate the accuracy of our ns-3 module via simulations against 3GPP calibration results

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arXiv2023

Improving the Efficiency of MIMO Simulations in ns-3

Channel modeling is a fundamental task for the design and evaluation of wireless technologies and networks, before actual prototyping, commercial product development and real deployments. The recent trends of current and future mobile networks, which include large antenna systems, massive deployments, and high-frequency bands, require complex channel models for the accurate simulation of massive MIMO in mmWave and THz bands. To address the complexity/accuracy trade-off, a spatial channel model has been defined by 3GPP (TR 38.901), which has been shown to be the main bottleneck of current system-level simulations in ns-3. In this paper, we focus on improving the channel modeling efficiency for large-scale MIMO system-level simulations. Extensions are developed in two directions. First, we improve the efficiency of the current 3GPP TR 38.901 implementation code in ns-3, by allowing the use of the Eigen library for more efficient matrix algebra operations, among other optimizations and a more modular code structure. Second, we propose a new performance-oriented MIMO channel model for reduced complexity, as an alternative model suitable for mmWave}/THz bands, and calibrate it against the 3GPP TR 38.901 model. Simulation results demonstrate the proper calibration of the newly introduced model for various scenarios and channel conditions, and exhibit an effective reduction of the simulation time (up to 16 times compared to the previous baseline) thanks to the various proposed improvements.

cs.NI↗

arXiv2023

ns-3 Implementation of Sub-Terahertz and Millimeter Wave Drop-based NYU Channel Model (NYUSIM)

The next generation of wireless networks will use sub-THz frequencies alongside mmWave frequencies to enable multi-Gbps and low-latency applications. To enable different verticals and use cases, engineers must take a holistic approach to build, analyze, and study different parts of the network and the interplay among the lower and higher layers of the protocol stack. It is of paramount importance to accurately characterize the radio propagation in diverse scenarios such as urban microcell (UMi), urban macrocell (UMa), rural macrocell (RMa), indoor hotspot (InH), and indoor factory (InF) for a wide range of frequencies. The 3GPP statistical channel model (SCM) is oversimplified and restricted to the frequency range of 0.5-100 GHz. Thus, to overcome these limitations, this paper presents a detailed implementation of the drop-based NYU channel model (NYUSIM) for the frequency range of 0.5-150 GHz for the UMi, UMa, RMa, InH, and InF scenarios. NYUSIM allows researchers to design and evaluate new algorithms and protocols for future sub-THz wireless networks in ns-3.

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arXiv2023

A Markov Game of Age of Information From Strategic Sources With Full Online Information

We investigate the performance of concurrent remote sensing from independent strategic sources, whose goal is to minimize a linear combination of the freshness of information and the updating cost. In the literature, this is often investigated from a static perspective of setting the update rate of the sources a priori, either in a centralized optimal way or with a distributed game-theoretic approach. However, we argue that truly rational sources would better make such a decision with full awareness of the current age of information, resulting in a more efficient implementation of the updating policies. To this end, we investigate the scenario where sources independently perform a stateful optimization of their objective. Their strategic character leads to the formalization of this problem as a Markov game, for which we find the resulting Nash equilibrium. This can be translated into practical smooth threshold policies for their update. The results are eventually tested in a sample scenario, comparing a centralized optimal approach with two distributed approaches with different objectives for the players.

cs.GT↗

arXiv2023

Downlink TDMA Scheduling for IRS-aided Communications with Block-Static Constraints

Intelligent reflecting surfaces (IRSs) are being studied as possible low-cost energy-efficient alternatives to active relays, with the goal of solving the coverage issues of millimeter wave (mmWave) and terahertz (THz) network deployments. In the literature, these surfaces are often studied by idealizing their characteristics. Notably, it is often assumed that IRSs can tune with arbitrary frequency the phase-shifts induced by their elements, thanks to a wire-like control channel to the next generation node base (gNB). Instead, in this work we investigate an IRS-aided time division multiple access (TDMA) cellular network, where the reconfiguration of the IRS may entail an energy or communication cost, and we aim at limiting the number of reconfigurations over time. We develop a clustering-based heuristic scheduling, which optimizes the system sum-rate subject to a given number of reconfigurations within the TDMA frame. To such end, we first cluster user equipments (UEs) with a similar optimal IRS configuration. Then, we compute an overall IRS cluster configuration, which can be thus kept constant while scheduling the whole UEs cluster. Numerical results show that our approach is effective in supporting IRSs-aided systems with practical constraints, achieving up to 85% of the throughput obtained by an ideal deployment, while providing a 50% reduction in the number of IRS reconfigurations.

eess.SP↗

arXiv2023

Safehaul: Risk-Averse Learning for Reliable mmWave Self-Backhauling in 6G Networks

Wireless backhauling at millimeter-wave frequencies (mmWave) in static scenarios is a well-established practice in cellular networks. However, highly directional and adaptive beamforming in today's mmWave systems have opened new possibilities for self-backhauling. Tapping into this potential, 3GPP has standardized Integrated Access and Backhaul (IAB) allowing the same base station serve both access and backhaul traffic. Although much more cost-effective and flexible, resource allocation and path selection in IAB mmWave networks is a formidable task. To date, prior works have addressed this challenge through a plethora of classic optimization and learning methods, generally optimizing a Key Performance Indicator (KPI) such as throughput, latency, and fairness, and little attention has been paid to the reliability of the KPI. We propose Safehaul, a risk-averse learning-based solution for IAB mmWave networks. In addition to optimizing average performance, Safehaul ensures reliability by minimizing the losses in the tail of the performance distribution. We develop a novel simulator and show via extensive simulations that Safehaul not only reduces the latency by up to 43.2% compared to the benchmarks but also exhibits significantly more reliable performance (e.g., 71.4% less variance in achieved latency).

cs.NI↗

arXiv2022

End-to-End Simulation of 5G Networks Assisted by IRS and AF Relays

The high propagation and penetration loss experienced at millimeter wave (mmWave) frequencies requires ultra-dense deployments of 5th generation (5G) base stations, which may be infeasible and costly for network operators. Integrated Access and Backhaul (IAB) has been proposed to partially address this issue, even though raising concerns in terms of power consumption and scalability. Recently, the research community has been investigating Intelligent Reflective Surfaces (IRSs) and Amplify-and-Forward (AF) relays as more energy-efficient alternatives to solve coverage issues in 5G scenarios. Along these lines, this paper relies on a new simulation framework, based on ns-3, to simulate IRS/AF systems with a full-stack, end-to-end perspective, with considerations on to the impact of the channel model and the protocol stack of 5G NR networks. Our goal is to demonstrate whether these technologies can be used to relay 5G traffic requests and, if so, how to dimension IRS/AF nodes as a function of the number of end users.

cs.NI↗

arXiv2021

5G NR-Light at Millimeter Waves: Design Guidelines for Mid-Market IoT Use Cases

5th generation (5G) systems have been designed with three main objectives in mind: increasing throughput, reducing latency, and enabling reliable communications. To meet these (often conflicting) constraints, the 3GPP released a set of specifications for 5G NR, one of the main innovations being the support for communications in the millimeter wave (mmWave) bands. However, how to implement lower complexity, energy efficient, mid-market Internet of Things (IoT) applications is still an on-going investigation, currently led by the 3GPP which is extending the NR standard with NR-Light specifications to support devices with reduced capabilities (REDCAP). While REDCAP devices may also operate at mmWaves to improve the network performance, hardware/software simplifications are needed to support balanced and mixed requirements compared to 5G NR systems. In this context, the contributions of this paper are threefold. First, we present some NR-Light use cases for which the support of the mmWave bands is desirable. Second, we describe how 5G NR can be simplified to achieve NR-Light requirements and expectations. Finally, we evaluate via simulation the performance of NR-Light devices operating at mmWaves in an industrial IoT setup, in terms of cost and complexity, throughput, and latency.

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arXiv2021

Resource Management for 5G NR Integrated Access and Backhaul: a Semi-centralized Approach

The next generations of mobile networks will be deployed as ultra-dense networks, to match the demand for increased capacity and the challenges that communications in the higher portion of the spectrum (i.e., the mmWave band) introduce. Ultra-dense networks, however, require pervasive, high-capacity backhaul solutions, and deploying fiber optic to all base stations is generally considered to be too expensive for network operators. The 3rd Generation Partnership Project (3GPP) has thus introduced Integrated Access and Backhaul (IAB), a wireless backhaul solution in which the access and backhaul links share the same hardware, protocol stack, and also spectrum. The multiplexing of different links in the same frequency bands, however, introduces interference and capacity sharing issues, thus calling for the introduction of advanced scheduling and coordination schemes. This paper proposes a semi-centralized resource allocation scheme for IAB networks, designed to be flexible, with low complexity, and compliant with the 3GPP IAB specifications. We develop a version of the Maximum Weighted Matching (MWM) problem that can be applied on a spanning tree that represents the IAB network and whose complexity is linear in the number of IAB-nodes. The proposed solution is compared with state-of-the-art distributed approaches through end-to-end, full-stack system-level simulations with a 3GPP-compliant channel model, protocol stack, and a diverse set of user applications. The results show how that our scheme can increase the throughput of cell-edge users up to 5 times, while decreasing the overall network congestion with an end-to-end delay reduction of up to 25 times.

cs.NI↗

arXiv2020

Enabling RAN Slicing Through Carrier Aggregation in mmWave Cellular Networks

The ever increasing number of connected devices and of new and heterogeneous mobile use cases implies that 5G cellular systems will face demanding technical challenges. For example, Ultra-Reliable Low-Latency Communication (URLLC) and enhanced Mobile Broadband (eMBB) scenarios present orthogonal Quality of Service (QoS) requirements that 5G aims to satisfy with a unified Radio Access Network (RAN) design. Network slicing and mmWave communications have been identified as possible enablers for 5G. They provide, respectively, the necessary scalability and flexibility to adapt the network to each specific use case environment, and low latency and multi-gigabit-per-second wireless links, which tap into a vast, currently unused portion of the spectrum. The optimization and integration of these technologies is still an open research challenge, which requires innovations at different layers of the protocol stack. This paper proposes to combine them in a RAN slicing framework for mmWaves, based on carrier aggregation. Notably, we introduce MilliSlice, a cross-carrier scheduling policy that exploits the diversity of the carriers and maximizes their utilization, thus simultaneously guaranteeing high throughput for the eMBB slices and low latency and high reliability for the URLLC flows.

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