arXiv subjects

Andrea Munari

Publications and source records attributed to Andrea Munari.

At least 19 recordsLinked to original sources

arXiv2026

A Spatio-Temporal Model for Information Freshness in Massive Random Access

Massive connectivity, a key building block of 5G, is expected to play an important role in the next generation of wireless systems, and its expected requirements are being revolutionized through the modeling of the information dynamics related to the vast numbers of Internet of things (IoT) devices. Motivated by this, the present paper introduces a model that captures the spatio-temporal nature of freshness of information sent via random access channel policies from an extremely large set of IoT devices via simple scalar parameters, i.e., the probability of success and accuracy of received updates. There are many information freshness metrics, starting from the age of information (AoI), all of which are proxies for the actual application performance, characterized over the temporal dimension. Our model adds the spatial dimension to this picture, observing that sensors distributed over the same area may have a strong correlation, and information from multiple close-by sensors may improve the overall accuracy of the receiver. We focus on characterizing the uncertainty of the receiver, expressed through the conditional entropy, considering a network of partially reliable, spatially distributed sensors observing the same process and reporting their measurements over a slotted ALOHA channel. We consider a simple forgetful receiver and a more complete model which accounts for the full history of past observations, deriving their performance, and optimizing the transmission probability of nodes to minimize the expected uncertainty.

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arXiv2026

Push-Pull Medium Access for Digital Twin Alignment and Low-Latency Anomaly Reporting

A digital twin (DT) contains a set of virtual models of real systems and processes that are synchronized with their physical counterparts. In a setup in which contact with the physical world is maintained through sensors and actuators that are wirelessly connected to the DT's computing engine, DT alignment requires periodic status updates, while safety-critical messages and fault conditions call for low-latency anomaly reporting, creating a fundamental trade-off in how wireless resources are used. We present a medium access framework combining pull-based updates, centrally scheduled according to goal-oriented principles, with urgent push-based updates, for which transmission decisions are made directly by the sensors. This enables the system to quickly detect and recover from anomalies while maintaining DT alignment. We thus design a push-pull scheduler (PPS) that strikes a balance in the trade-off between DT alignment in normal conditions and anomaly reporting, optimizing resource usage and reducing DT drift by 20 - 30% with respect to state-of-the-art solutions while maintaining the same anomaly detection guarantees, or reducing worst-case anomaly detection times by 30 - 70% while meeting the same DT alignment conditions.

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arXiv2026

Two-Step Interference Cancellation for Energy Saving in Irregular Repetition Slotted ALOHA

We evaluate a modification of irregular repetition slotted ALOHA (IRSA) involving intermediate decoding and early transmission termination by some nodes, upon their decoding success. This is meant to avoid unnecessary transmissions, thereby reducing energy consumption. We expect this to be particularly useful at low loads, where most transmissions can be avoided as they do not often result in a collision and are therefore redundant. To validate this proposal, we observe that most of the literature related to IRSA considers an asymptotic heavily loaded regime; thus, we also present a model of energy consumption and success probability for frames of limited length and low offered loads. Thanks to our analysis, also confirmed by simulation, we are able to show that the proposed technique is able to reduce IRSA energy consumption by minimizing transmissions, while preserving performance gains over standard ALOHA. For example, we are able to get a 33% energy saving at offered loads around 10% without affecting throughput.

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arXiv2025

To Share, or Not to Share: A Study on GEO-LEO Systems for IoT Services with Random Access

The increasing number of satellite deployments, both in the low and geostationary Earth orbit exacerbates the already ongoing scarcity of wireless resources when targeting ubiquitous connectivity. For the aim of supporting a massive number of IoT devices characterized by bursty traffic and modern variants of random access, we pose the following question: Should competing satellite operators share spectrum resources or is an exclusive allocation preferable? This question is addressed by devising a communication model for two operators which serve overlapping coverage areas with independent IoT services. Analytical approximations, validated by Monte Carlo simulations, reveal that spectrum sharing can yield significant throughput gains for both operators under certain conditions tied to the relative serviced user populations and coding rates in use. These gains are sensitive also to the system parameters and may not always render the spectral coexistence mutually advantageous. Our model captures basic trade-offs in uplink spectrum sharing and provides novel actionable insights for the design and regulation of future 6G non-terrestrial networks.

eess.SP↗

arXiv2025

On the Role of Early-Termination for Age of Information in Tree-Based Random Access Protocols

Age of Information (AoI) has emerged as a key metric for assessing data freshness in IoT applications, where a large number of devices report time-stamped updates to a monitor. Such systems often rely on random access protocols based on variations of ALOHA at the link layer, where collision resolution algorithms play a fundamental role to enable reliable delivery of packets. In this context, we provide the first analytical characterization of average AoI for the classical Capetanakis tree-based algorithm with gated access under exogenous traffic, capturing the protocol's dynamics, driven by sporadic packet generation and variable collision resolution times. We also explore a variant with early termination, where contention is truncated after a maximum number of slots even if not all users are resolved. The approach introduces a fundamental trade-off between reliability and timeliness, allowing stale packets to be dropped to improve freshness.

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arXiv2025

Spatio-Temporal Information Freshness for Remote Source Monitoring in IoT Systems

The widespread adoption of age of information (AoI) as a meaningful and analytically tractable information freshness metric has led to a wide body of work on the timing performance of Internet of things (IoT) systems. However, the spatial correlation inherent to environmental monitoring has been mostly neglected in the recent literature, due to the significant modeling complexity it introduces. In this work, we address this gap by presenting a model of spatio-temporal information freshness, considering the conditional entropy of the system state in a remote monitoring scenario, such as a low-orbit satellite collecting information from a wide geographical area. Our analytical results show that purely age-oriented schemes tend to select an overly broad communication range, leading to inaccurate estimates and energy inefficiency, both of which can be mitigated by adopting a spatio-temporal approach.

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arXiv2025

Goal-Oriented Medium Access with Distributed Belief Processing

Goal-oriented communication entails the timely transmission of updates related to a specific goal defined by the application. In a distributed setup with multiple sensors, each individual sensor knows its own observation and can determine its freshness, as measured by Age of Incorrect Information (AoII). This local knowledge is suited for distributed medium access, where the transmission strategies have to deal with collisions. We present Dynamic Epistemic Logic for Tracking Anomalies (DELTA), a medium access protocol that limits collisions and minimizes AoII in anomaly reporting over dense networks. Each sensor knows its own AoII, while it can compute the belief about the AoII for all other sensors, based on their Age of Information (AoI), which is inferred from the acknowledgments. This results in a goal-oriented approach based on dynamic epistemic logic emerging from public information. We analyze the resulting DELTA protocol both from a theoretical standpoint and with Monte Carlo simulations, showing that it is significantly more efficient and robust than classical random access, while outperforming state-of-the-art scheduled schemes by at least 30%, even with imperfect feedback.

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arXiv2025

A low-PAPR Pilot Design and Optimization for OTFS Modulation

Orthogonal time frequency space (OTFS) modulation has been proposed recently as a new waveform in the context of doubly-selective multi-path channels. This article proposes a novel pilot design that improves OTFS spectral efficiency (SE) while reducing its peak-to-average power ratio (PAPR). Instead of adopting an embedded data-orthogonal pilot for channel estimation, our scheme relies on Chu sequences superimposed to data symbols. We optimize the construction by investigating the best energy split between pilot and data symbols. Two equalizers, and an iterative channel estimation and equalization procedure are considered. We present extensive numerical results of relevant performance metrics, including the normalized mean squared error of the estimator, bit error rate, PAPR and SE. Our results show that, while the embedded pilot scheme estimates the channel more accurately, our approach yields a better tradeoff by achieving much higher spectral efficiency and lower PAPR.

eess.SP↗

arXiv2025

Timely Status Updates in Slotted ALOHA Networks With Energy Harvesting

We investigate the age of information (AoI) in a scenario where energy-harvesting devices send status updates to a gateway following the slotted ALOHA protocol and receive no feedback. We let the devices adjust the transmission probabilities based on their current battery level. Using a Markovian analysis, we derive analytically the average AoI. We further provide an approximate analysis for accurate and easy-to-compute approximations of both the average AoI and the age-violation probability (AVP), i.e., the probability that the AoI exceeds a given threshold. We also analyze the average throughput. Via numerical results, we investigate two baseline strategies: transmit a new update whenever possible to exploit every opportunity to reduce the AoI, and transmit only when sufficient energy is available to increase the chance of successful decoding. The two strategies are beneficial for low and high update-generation rates, respectively. We show that an optimized policy that balances the two strategies outperforms them significantly in terms of both AoI metrics and throughput. Finally, we show the benefit of decoding multiple packets in a slot using successive interference cancellation and adapting the transmission probability based on both the current battery level and the time elapsed since the last transmission.

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arXiv2025

On the Uncertainty of a Simple Estimator for Remote Source Monitoring over ALOHA Channels

Efficient remote monitoring of distributed sources is essential for many Internet of Things (IoT) applications. This work studies the uncertainty at the receiver when tracking two-state Markov sources over a slotted random access channel without feedback, using the conditional entropy as a performance indicator, and considering the last received value as current state estimate. We provide an analytical characterization of the metric, and evaluate three access strategies: (i) maximizing throughput, (ii) transmitting only on state changes, and (iii) minimizing uncertainty through optimized access probabilities. Our results reveal that throughput optimization does not always reduce uncertainty. Moreover, while reactive policies are optimal for symmetric sources, asymmetric processes benefit from mixed strategies allowing transmissions during state persistence.

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arXiv2024

Peak Age of Incorrect Information of Reactive ALOHA Reporting Under Imperfect Feedback

Age of Incorrect Information (AoII) is particularly relevant in systems where real time responses to anomalies are required, such as natural disaster alerts, cybersecurity warnings, or medical emergency notifications. Keeping system control with wrong information for too long can lead to inappropriate responses. In this paper, we study the Peak AoII (PAoII) for multi-source status reporting by independent devices over a collision channel, following a zero-threshold ALOHA access where nodes observing an anomaly immediately start transmitting about it. If a collision occurs, nodes reduce the transmission probability to allow for a resolution. Finally, wrong or lost feedback messages may lead a node that successfully updated the destination to believe a collision happened. The PAoII for this scenario is computed in closed-form. We are eventually able to derive interesting results concerning the minimization of PAoII, which can be traded against the overall goodput and energy efficiency, but may push the system to the edge of congestion collapse.

cs.NI↗

arXiv2024

Age-of-Gradient Updates for Federated Learning over Random Access Channels

This paper studies the problem of federated training of a deep neural network (DNN) over a random access channel (RACH) such as in computer networks, wireless networks, and cellular systems. More precisely, a set of remote users participate in training a centralized DNN model using SGD under the coordination of a parameter server (PS). The local model updates are transmitted from the remote users to the PS over a RACH using a slotted ALOHA protocol. The PS collects the updates from the remote users, accumulates them, and sends central model updates to the users at regular time intervals. We refer to this setting as the RACH-FL setting. The RACH-FL setting crucially addresses the problem of jointly designing a (i) client selection and (ii) gradient compression strategy which addresses the communication constraints between the remote users and the PS when transmission occurs over a RACH. For the RACH-FL setting, we propose a policy, which we term the ''age-of-gradient'' (AoG) policy in which (i) gradient sparsification is performed using top-K sparsification, (ii) the error correction is performed using memory accumulation, and (iii) the slot transmission probability is obtained by comparing the current local memory magnitude minus the magnitude of the gradient update to a threshold. Intuitively, the AoG measure of ''freshness'' of the memory state is reminiscent of the concept of age-of-information (AoI) in the context of communication theory and provides a rather natural interpretation of this policy. Numerical simulations show the superior performance of the AoG policy as compared to other RACH-FL policies.

cs.LG↗

arXiv2024

Evolution of the 5G New Radio Two-Step Random Access towards 6G Unsourced MAC

This report summarizes some considerations on possible evolutions of grant-free random access in the next generation of the 3GPP wireless cellular standard. The analysis is carried out by mapping the problem to the recently-introduced unsourced multiple access channel (UMAC) setup. By doing so, the performance of existing solutions can be benchmarked with information-theoretic bounds, assessing the potential gains that can be achieved over legacy 3GPP schemes. The study focuses on the two-step random access (2SRA) protocol introduced by Release 16 of the 5G New Radio standard, investigating its applicability to support large MTC / IoT terminal populations in a grant-free fashion. The analysis shows that the existing 2SRA scheme may not succeed in providing energy-efficient support to large user populations. Modifications to the protocol are proposed that enable remarkable gains in both energy and spectral efficiency while retaining a strong resemblance to the legacy protocol.

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arXiv2023

Remote Monitoring of Two-State Markov Sources via Random Access Channels: an Information Freshness vs. State Estimation Entropy Perspective

We study a system in which two-state Markov sources send status updates to a common receiver over a slotted ALOHA random access channel. We characterize the performance of the system in terms of state estimation entropy (SEE), which measures the uncertainty at the receiver about the sources' state. Two channel access strategies are considered: a reactive policy that depends on the source behaviour and a random one that is independent of it. We prove that the considered policies can be studied using two different hidden Markov models and show through a density evolution analysis that the reactive strategy outperforms the random one in terms of SEE while the opposite is true for age of information. Furthermore, we characterize the probability of error in the state estimation at the receiver, considering a maximum a posteriori and a low-complexity (decode & hold) estimator. Our study provides useful insights on the design trade-offs that emerge when different performance metrics are adopted. Moreover, we show how the source statistics significantly impact the system performance.

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arXiv2023

Timely and Efficient Information Delivery in Real-Time Industrial IoT Networks

Enabling real-time communication in Industrial Internet of Things (IIoT) networks is crucial to support autonomous, self-organized and re-configurable industrial automation for Industry 4.0 and the forthcoming Industry 5.0. In this paper, we consider a SIC-assisted real-time IIoT network, in which sensor nodes generate reports according to an event-generation probability that is specific for the monitored phenomena. The reports are delivered over a block-fading channel to a common Access Point (AP) in slotted ALOHA fashion, which leverages the imbalances in the received powers among the contending users and applies successive interference cancellation (SIC) to decode user packets from the collisions. We provide an extensive analytical treatment of the setup, deriving the Age of Information (AoI), throughput and deadline violation probability, when the AP has access to both the perfect as well as the imperfect channel-state information. We show that adopting SIC improves all the performance parameters with respect to the standard slotted ALOHA, as well as to an age-dependent access method. The analytical results agree with the simulation based ones, demonstrating that investing in the SIC capability at the receiver enables this simple access method to support timely and efficient information delivery in IIoT networks.

cs.NI↗

arXiv2023

Age of Information in Slotted ALOHA With Energy Harvesting

We examine the age of information (AoI) of a status update system that incorporates energy harvesting and uses the slotted ALOHA protocol. We derive analytically the average AoI and the probability that the AoI exceeds a given threshold. Via numerical results, we investigate two strategies to minimize the age of information (AoI): transmitting a new update whenever possible to exploit every chance to reduce the AoI, and transmitting only when sufficient energy is available to increase the chance of successful delivery. The two strategies are beneficial for low and high update generation rates, respectively. However, an optimized approach that balances the two strategies outperforms them significantly in terms of both AoI and throughput.

cs.IT↗

arXiv2023

The Dynamic Behavior of Frameless ALOHA: Drift Analysis, Throughput, and Age of Information

We study the dynamic behavior of frameless ALOHA, both in terms of throughput and age of information (AoI). In particular, differently from previous studies, our analysis accounts for the fact that the number of terminals contending the channel may vary over time, as a function of the duration of the previous contention period. The stability of the protocol is analyzed via a drift analysis, which allows us to determine the presence of stable and unstable equilibrium points. We also provide an exact characterization of the AoI performance, through which we determine the impact of some key protocol parameters, such as the maximum length of the contention period, on the average AoI. Specifically, we show that configurations of parameters that maximize the throughput may result in a degradation of the AoI performance.

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arXiv2023

Age of Incorrect Information in Random Access Channels without Feedback

We focus on a system in which a set of two-state Markov sources report status update to a common receiver over a shared wireless channel. Inspired by practical IoT networks, we consider three variations of ALOHA as medium access protocol: i) a random approach in which a source transmits regardless of its status, ii) a reactive scheme in which updates are sent only when a source changes state, and iii) a hybrid solution which blends the two possibilities. We consider different criteria to capture the ability of the receiver to maintain an accurate perception of the tracked processes: average age of incorrect information (AoII), probability of missed detection (i.e., of not detecting a source transition), and average duration of intervals over which the receiver lingers with erroneous knowledge. We provide closed form analytical expressions for all the metrics, highlighting non-trivial trade-offs and providing useful protocol design hints.

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