arXiv subjects

Nicola Marchetti

Publications and source records attributed to Nicola Marchetti.

At least 37 records · Page 2Linked to original sources

arXiv2025

Notes on Degeneracy and Robustness

Degeneracy is the ability of structurally different elements to perform the same function or yield the same output under certain constraints. In contrast to redundancy, which implies identical backups, degeneracy allows diverse components to step in and perform the same or similar role. Mathematically, it is about mapping multiple distinct elements into the same function. In a degenerate system, failure in one part can be compensated by others not structurally linked. System functions are distributed within the system itself or the entire network. This renders faster and more adaptive recovery. In this work, we define and formulate several novel metrics for resource fungibility to address robustness in networks (static/mobile/dynamic).

cs.NI↗

arXiv2025

Mitigating xApp conflicts for efficient network slicing in 6G O-RAN: a graph convolutional-based attention network approach

O-RAN (Open-Radio Access Network) offers a flexible, open architecture for next-generation wireless networks. Network slicing within O-RAN allows network operators to create customized virtual networks, each tailored to meet the specific needs of a particular application or service. Efficiently managing these slices is crucial for future 6G networks. O-RAN introduces specialized software applications called xApps that manage different network functions. In network slicing, an xApp can be responsible for managing a separate network slice. To optimize resource allocation across numerous network slices, these xApps must coordinate. Traditional methods where all xApps communicate freely can lead to excessive overhead, hindering network performance. In this paper, we address the issue of xApp conflict mitigation by proposing an innovative Zero-Touch Management (ZTM) solution for radio resource management in O-RAN. Our approach leverages Multi-Agent Reinforcement Learning (MARL) to enable xApps to learn and optimize resource allocation without the need for constant manual intervention. We introduce a Graph Convolutional Network (GCN)-based attention mechanism to streamline communication among xApps, reducing overhead and improving overall system efficiency. Our results compare traditional MARL, where all xApps communicate, against our MARL GCN-based attention method. The findings demonstrate the superiority of our approach, especially as the number of xApps increases, ultimately providing a scalable and efficient solution for optimal network slicing management in O-RAN.

cs.NI↗

arXiv2025

Distributed Time Synchronization in NOMA-Assisted Ultra-Dense Networks

Ultra-dense networks (UDNs) represent a transformative access architecture for upcoming sixth generation (6G) systems, poised to meet the surging demand for high data rates. Achieving precise synchronization across diverse base stations (BSs) is critical in these networks to mitigate inter-cell interference (ICI). However, traditional centralized synchronization approaches face substantial challenges in dense urban, including limited access to Global Positioning System (GPS), dependence on reliable backhaul, and high signaling overhead demands. This study advances a low-complexity distributed synchronization solution. A primary focus is on assessing the algorithm's accuracy incorporating the effects of information exchange delays, which are pronounced in large-networks. Recognizing the pivotal role of neighbor-gathered information in the proposed approach, this research employs uplink Non-Orthogonal Multiple Access (NOMA) to reduce message-gathering delays between transmitters (TXs) and receivers (RXs). The proposed algorithm is evaluated to assess effectiveness under exchange delays, analyzing impact of system parameters like network connectivity, size, sub-bands, etc., on synchronization speed. The findings demonstrate that the NOMA-based information-gathering technique significantly accelerates network synchronization compared to orthogonal access schemes. This advancement is crucial for meeting the low-latency requirements of beyond fifth generation (5G) systems, underscoring the potential of distributed synchronization as a cornerstone for next-generation UDN deployments.

cs.MA↗

arXiv2024

Optimized Topology Control for IoT Networks using Graph-based Localization

The key research question we are addressing in this paper, is how local distance information can be integrated into the global structure determination, in the form of network graphs realization for IoT networks. IoT networks will be pervading every walk of life over the next few years with the aim of improving quality of life and enhancing surrounding living conditions, while balancing available resources, like energy and computational power. As we deal with massive number of heterogeneous devices contributing to each IoT network, it is of paramount importance that the IoT network topology can be designed and controlled in such a way that coverage and throughput can be maximized using a minimum number of devices, while tackling challenges like poor link quality and interference. We tackle the above-mentioned problem of topology design and control through our designed graph-realization concept. End-nodes and gateways are identified and placed within neighborhood sub-graphs and their own coordinate system, which are stitched together to form the global graph. The stitching is done in a way that transmit power and information rate are optimized while reducing error probability.

eess.SY↗

arXiv2024

Quantum Game Theory meets Quantum Networks

Classical game theory is a powerful tool focusing on optimized resource distribution, allocation and sharing in classical wired and wireless networks. As quantum networks are emerging as a means of providing true connectivity between quantum computers, it is imperative and crucial to exploit game theory for addressing challenges like entanglement distribution and access, routing, topology extraction and inference for quantum networks. Quantum networks provide the promising opportunity of employing quantum games owing to their inherent capability of generating and sharing quantum states. Besides, quantum games offer enhanced payoffs and winning probabilities, new strategies and equilibria, which are unimaginable in classical games. Employing quantum game theory to solve fundamental challenges in quantum networks opens a new fundamental research direction necessitating inter-disciplinary efforts. In this article, we introduce a novel game-theoretical framework for exploiting quantum strategies to solve, as archetypal example, one of the key functionality of a quantum network, namely, the entanglement distribution. We compare the quantum strategies with classical ones by showing the quantum advantages in terms of link fidelity improvement and latency decrease in communication. In future, we will generalize our game framework to optimize entanglement distribution and access over any quantum network topology. We will also explore how quantum games can be leveraged to address other challenges like routing, optimization of quantum operations and topology design.

cs.NI↗

arXiv2024

Testing Link Fidelity in a Quantum Network using Operational Form of Trace Distance with Error Bounds

Quantum state comparison, utilizing metrics like fidelity and trace distance, underpins the assessment of quantum networks within quantum information theory. While recent research has expanded theoretical understanding, incorporating error analysis and scalability considerations remains crucial for practical applications. The primary contribution of this letter is to address these gaps by deriving the novel operational trace distance for multi-node networks, establishing a trace distance vs. fidelity benchmark incorporating error bounds, and bridging quantum operations with tensor network analysis. We further explore the application of tensor network tools to quantum networks, offering new analytical avenues. This comprehensive approach provides a robust framework for evaluating quantum network performance under realistic error conditions, facilitating the development of reliable quantum technologies.

math.QA↗

arXiv2023

Pattern and Polarization Diversity Multi-Sector Annular Antenna for IoT Applications

This work proposes a small pattern and polarization diversity multi-sector annular antenna with electrical size and profile of ${ka=1.2}$ and ${0.018λ}$, respectively. The antenna is planar and comprises annular sectors that are fed using different ports to enable digital beamforming techniques, with efficiency and gain of up to 78% and 4.62 dBi, respectively. The cavity mode analysis is used to describe the design concept and the antenna diversity. The proposed method can produce different polarization states (e.g. linearly and circularly polarized patterns), and pattern diversity characteristics covering the elevation plane. Owing to its small electrical size, low-profile and diversity properties, the solution shows good promise to enable advanced radio applications like wireless physical layer security in many emerging and size-constrained Internet of Things (IoT) devices.

eess.SP↗

arXiv2023

Classical Capacity of Arbitrarily Distributed Noisy Quantum Channels

With the rapid deployment of quantum computers and quantum satellites, there is a pressing need to design and deploy quantum and hybrid classical-quantum networks capable of exchanging classical information. In this context, we conduct the foundational study on the impact of a mixture of classical and quantum noise on an arbitrary quantum channel carrying classical information. The rationale behind considering such mixed noise is that quantum noise can arise from different entanglement and discord in quantum transmission scenarios, like different memories and repeater technologies, while classical noise can arise from the coexistence with the classical signal. Towards this end, we derive the distribution of the mixed noise from a classical system's perspective, and formulate the achievable channel capacity over an arbitrary distributed quantum channel in presence of the mixed noise. Numerical results demonstrate that capacity increases with the increase in the number of photons per usage.

quant-ph↗

arXiv2023

Low-Complexity Dynamic Directional Modulation: Vulnerability and Information Leakage

In this paper, the privacy of wireless transmissions is improved through the use of an efficient technique termed dynamic directional modulation (DDM), and is subsequently assessed in terms of the measure of information leakage. Recently, a variation of DDM termed low-power dynamic directional modulation (LPDDM) has attracted significant attention as a prominent secure transmission method due to its ability to further improve the privacy of wireless communications. Roughly speaking, this modulation operates by randomly selecting the transmitting antenna from an antenna array whose radiation pattern is well known. Thereafter, the modulator adjusts the constellation phase so as to ensure that only the legitimate receiver recovers the information. To begin with, we highlight some privacy boundaries inherent to the underlying system. In addition, we propose features that the antenna array must meet in order to increase the privacy of a wireless communication system. Last, we adopt a uniform circular monopole antenna array with equiprobable transmitting antennas in order to assess the impact of DDM on the information leakage. It is shown that the bit error rate, while being a useful metric in the evaluation of wireless communication systems, does not provide the full information about the vulnerability of the underlying system.

cs.IT↗

arXiv2023

Semantic-Functional Communications in Cyber-Physical Systems

This paper explores the use of semantic knowledge inherent in the cyber-physical system (CPS) under study in order to minimize the use of explicit communication, which refers to the use of physical radio resources to transmit potentially informative data. It is assumed that the acquired data have a function in the system, usually related to its state estimation, which may trigger control actions. We propose that a semantic-functional approach can leverage the semantic-enabled implicit communication while guaranteeing that the system maintains functionality under the required performance. We illustrate the potential of this proposal through simulations of a swarm of drones jointly performing remote sensing in a given area. Our numerical results demonstrate that the proposed method offers the best design option regarding the ability to accomplish a previously established task -- remote sensing in the addressed case -- while minimising the use of radio resources by controlling the trade-offs that jointly determine the CPS performance and its effectiveness in the use of resources. In this sense, we establish a fundamental relationship between energy, communication, and functionality considering a given end application.

cs.IT↗

arXiv2023

IoT Localization and Optimized Topology Extraction Using Eigenvector Synchronization

Internet-of-Things (IoT) devices are low size, weight and power (SWaP), low complexity and include sensors, meters, wearables and trackers. Transmitting information with high signal power is exacting on device battery life, therefore an efficient link and network configuration is absolutely crucial to avoid signal power enhancement in interference-rich environment and resorting to battery-life extending strategies. Efficient network configuration can also ensure fulfilment of network performance metrics like throughput, coding rate and spectral efficiency. We formulate a novel approach of first localizing the IoT nodes and then extracting the network topology for information exchange between the nodes (devices, gateway and sinks), such that overall network throughput is maximized. The nodes are localized using noisy measurements of a subset of Euclidean distances between two nodes. Realizable subsets of neighboring devices agree with their own position within the entire network graph through eigenvector synchronization. Using communication global graph-model-based technique, network topology is constructed in terms of transmit power allocation with the aim of maximizing spatial usage and overall network throughput. This topology extraction problem is solved using the concept of linear programming.

eess.SP↗

arXiv2023

Wavelet Packet Division Multiplexing (WPDM)-Aided Industrial WSNs

Industrial Internet-of-Things (IIoT) involve multiple groups of sensors, each group sending its observations on a particular phenomenon to a central computing platform over a multiple access channel (MAC). The central platform incorporates a decision fusion center (DFC) that arrives at global decisions regarding each set of phenomena by combining the received local sensor decisions. Owing to the diverse nature of the sensors and heterogeneous nature of the information they report, it becomes extremely challenging for the DFC to denoise the signals and arrive at multiple reliable global decisions regarding multiple phenomena. The industrial environment represents a specific indoor scenario devoid of windows and filled with different noisy electrical and measuring units. In that case, the MAC is modelled as a large-scale shadowed and slowly-faded channel corrupted with a combination of Gaussian and impulsive noise. The primary contribution of this paper is to propose a flexible, robust and highly noise-resilient multi-signal transmission framework based on Wavelet packet division multiplexing (WPDM). The local sensor observations from each group of sensors are waveform coded onto wavelet packet basis functions before reporting them over the MAC. We assume a multi-antenna DFC where the waveform-coded sensor observations can be separated by a bank of linear filters or a correlator receiver, owing to the orthogonality of the received waveforms. At the DFC we formulate and compare fusion rules for fusing received multiple sensor decisions, to arrive at reliable conclusions regarding multiple phenomena. Simulation results show that WPDM-aided wireless sensor network (WSN) for IIoT environments offer higher immunity to noise by more than 10 times over performance without WPDM in terms of probability of false detection.

eess.SP↗

arXiv2023

A novel semantic-functional approach for multiuser event-trigger communication

This work introduces a new perspective for physical media sharing in multiuser communication by jointly considering (i) the meaning of the transmitted message and (ii) its function at the end user. Specifically, we have defined a scenario where multiple users (sensors) are continuously transmitting their own states concerning a predetermined event. On the receiver side there is an alarm monitoring system, whose function is to decide whether such a predetermined event has happened in a certain time period and, if yes, in which user. The media access control protocol proposed constitutes an alternative approach to the conventional physical layer methods, because the receiver does not decode the received waveform directly; rather, the relative position of the absence or presence of energy within a multidimensional resource space carries the (semantic) information. The protocol introduced here provides high efficiency in multiuser networks that operate with event-triggered sampling by enabling a constructive reconstruction of transmission collisions. We have demonstrated that the proposed method leads to a better event transmission efficiency than conventional methods like TDMA and slotted ALOHA. Remarkably, the proposed method achieves 100\% efficiency and 0\% error probability in almost all the studied cases, while consistently outperforming TDMA and slotted ALOHA.

cs.IT↗

arXiv2023

Entanglement Distribution and Quantum Teleportation in Higher Dimension over the Superposition of Causal Orders of Quantum Channels

Multiple photonic degrees of freedom can be explored to generate high-dimensional quantum states; commonly referred to as `qudits'. Qudits offer several advantages for quantum communications, including higher information capacity, noise resilience and data throughput, and lower information loss over different propagation mediums (free space, optical fibre, underwater) as compared to conventional qubits based communication system. However, qudits have been little exploited in literature, owing to their difficulty in transmission and detection. In this paper, for the first time, we develop and formulate the theoretical framework for transmission of classical information through entanglement distribution of qudits over two quantum channels in superposition of alternative causal order. For the first time we i) engineer quantum switch operation for 2-qudit systems and ii) formulate theoretical system model for entanglement distribution of qudits via quantum switch. Results show that entanglement distribution of a qudit provides a considerable gain in fidelity even with increase in noise.

quant-ph↗

arXiv2023

Dimensioning spectrum to support ultra-reliable low-latency communication

Industry-led initiatives such as the Next G Alliance (NGA) are currently considering how to dimension the spectrum required to support new classes of services envisioned beyond 5G. In particular, support for URLLC brings the challenge of how to dimension stochastic wireless networks to meet stringent reliability and latency requirements. Our analysis indicates that the bandwidth needed to meet URLLC goals can be in the order of gigahertz, beyond what is available in today's mobile networks. Network densification can ease those bandwidth needs but requires new deployment strategies involving substantially larger numbers of sites. As an alternative, we consider multi-connectivity and multi-operator network sharing as efficient ways to reduce the demand for bandwidth without outright deployment of additional base stations.

cs.NI↗

arXiv2023

Quantum Channel Modelling by Statistical Quantum Signal Processing

In this paper we are interested to model quantum signal by statistical signal processing methods. The Gaussian distribution has been considered for the input quantum signal as Gaussian state have been proven to a type of important robust state and most of the important experiments of quantum information are done with Gaussian light. Along with that a joint noise model has been invoked, and followed by a received signal model has been formulated by using convolution of transmitted signal and joint quantum noise to realized theoretical achievable capacity of the single quantum link. In joint quantum noise model we consider the quantum Poisson noise with classical Gaussian noise. We compare the capacity of the quantum channel with respect to SNR to detect its overall tendency. In this paper we use the channel equation in terms of random variable to investigate the quantum signals and noise model statistically. These methods are proposed to develop Quantum statistical signal processing and the idea comes from the statistical signal processing.

quant-ph↗

arXiv2023

Mathematical Model of Quantum Channel Capacity

In this article, we are proposing a closed-form solution for the capacity of the single quantum channel. The Gaussian distributed input has been considered for the analytical calculation of the capacity. In our previous couple of papers, we invoked models for joint quantum noise and the corresponding received signals; in this current research, we proved that these models are Gaussian mixtures distributions. In this paper, we showed how to deal with both of cases, namely (I)the Gaussian mixtures distribution for scalar variables and (II) the Gaussian mixtures distribution for random vectors. Our target is to calculate the entropy of the joint noise and the entropy of the received signal in order to calculate the capacity expression of the quantum channel. The main challenge is to work with the function type of the Gaussian mixture distribution. The entropy of the Gaussian mixture distributions cannot be calculated in the closed-form solution due to the logarithm of a sum of exponential functions. As a solution, we proposed a lower bound and a upper bound for each of the entropies of joint noise and the received signal, and finally upper inequality and lower inequality lead to the upper bound for the mutual information and hence the maximum achievable data rate as the capacity. In this paper reader will able to visualize an closed-form capacity experssion which make this paper distinct from our previous works. These capacity experssion and coresses ponding bounds are calculated for both the cases: the Gaussian mixtures distribution for scalar variables and the Gaussian mixtures distribution for random vectors as well.

cs.IT↗

arXiv2023

Electrically Small Multimodal 3D Beamforming MIMO Antenna for PHY-Layer Security

This work proposes an electrically small 3D beamforming antenna for PHYsical Layer (PHY-layer) security. The antenna comprises two layers of stacked patch structures and is a five-mode five-port MIMO system operating around 1.85 GHz with electrical size ${ka=0.98}$ and radiation efficiency of up to ${55\%}$. By studying the properties of the excited modes, phase and amplitude control allow for unidirectional beam scanning towards any direction around the elevation and azimuth planes. PHY-layer security is investigated using the directional modulation (DM) technique, which transmits unscrambled baseband constellation symbols to a pre-specified secure direction while simultaneously spatially distorting the same constellations in all other directions. Bit Error Rate (BER) calculations reveal very low values of ${2\times10^{-5}}$ for the desired direction of the legitimate receiver, with BER${<10^{-2}}$ beamwidths of ${55^{\circ}}$ and ${58^{\circ}}$ for the azimuth and elevation planes, respectively.

eess.SP↗