arXiv subjects

Marco Chiani

Publications and source records attributed to Marco Chiani.

At least 37 records · Page 2Linked to original sources

arXiv2023

Interference Cancellation Algorithms for Grant-Free Multiple Access with Massive MIMO

In next generation Internet-of-Things, the overhead introduced by grant-based multiple access protocols may engulf the access network as a consequence of the unprecedented number of connected devices. Grant-free access protocols are therefore gaining an increasing interest to support massive access from machine-type devices with intermittent activity. In this paper, coded random access (CRA) with massive multiple input multiple output (MIMO) is investigated as a solution to design highly-scalable massive multiple access protocols, taking into account stringent requirements on latency and reliability. With a focus on signal processing aspects at the physical layer and their impact on the overall system performance, critical issues of successive interference cancellation (SIC) over fading channels are first analyzed. Then, SIC algorithms and a scheduler are proposed that can overcome some of the limitations of the current access protocols. The effectiveness of the proposed processing algorithms is validated by Monte Carlo simulation, for different CRA protocols and by comparisons with developed benchmarks.

eess.SP↗

arXiv2023

Performance Analysis of Quantum Error-Correcting Surface Codes over Asymmetric Channels

One of the main challenge for an efficient implementation of quantum information technologies is how to counteract quantum noise. Quantum error correcting codes are therefore of primary interest for the evolution towards quantum computing and quantum Internet. We here analyze the performance of surface codes, one of the most important class for practical implementations, on both symmetric and asymmetric quantum channels. We derive approximate expressions, confirmed by simulations, to evaluate the performance of surface codes and of XZZX codes, and provide a metric to assess the advantage of codes with respect to uncoded systems. Our findings allow to characterize the performance by means of analytical formulas of surface codes, like, for example, the [[13, 1, 3]], the [[23, 1, 3/5]], the [[33, 1, 3/7]], and the [[41, 1, 5]] surface codes.

quant-ph↗

arXiv2022

A Joint PHY and MAC Layer Design for Coded Random Access with Massive MIMO

Grant-free access schemes are candidates to support future massive multiple access applications owing to their capability to reduce control signaling and latency. As a promising class of grant-free schemes, coded random access schemes can achieve high reliabilities also with uncoordinated transmissions and therefore in presence packet collisions. In this paper, an analysis tool for coded random access, based on density evolution, is proposed and exploited for system design and optimization. In sharp contrast with the existing literature, where such tools have been developed under simplified channel assumptions, the proposed tool captures not only MAC layer features, but also the physical wireless fading channel and a realistic physical layer signal processing based on multiple antennas and randomly-chosen orthogonal pilots. Theoretical results are validated by comparison with symbol-level Monte Carlo simulations.

cs.IT↗

arXiv2022

Irregular Repetition Slotted ALOHA in an Information-Theoretic Setting

An information-theoretic approach to irregular repetition slotted ALOHA (IRSA) is proposed. In contrast with previous works, in which IRSA analysis is conducted only based on quantities that are typical of collision models such as the traffic, the new approach also captures more fundamental quantities. Specifically, a suitable codebook construction for the adder channel model is adopted to establish a link with successive interference cancellation over the multi-packet reception channel. This perspective allows proving achievability and converse results for the average sum rate of IRSA multiple access schemes.

cs.IT↗

arXiv2022

Two-Leg Deep Space Relay Architectures: Performance, Challenges, and Perspectives

In this paper, architectures for interplanetary communications that feature the use of a data relay are investigated. In the considered "two-leg" architecture, a spacecraft orbiting the Earth, or in orbit at a Lagrange point, receives data from a deep space probe (leg-1) and relays them towards ground (leg-2). Different wireless technologies for the interplanetary link, namely, radio frequencies above the Ka band and optical frequencies, are considered. Moreover, the cases of transparent and regenerative relaying as well as different different orbital configurations are addressed, offering a thorough analysis of such systems from different viewpoints. Results show that, under certain constraints in terms of pointing accuracy and onboard antenna size, the adoption of a two-leg architecture can achieve the data rates supported by direct space-to-Earth link configurations with remarkably smaller ground station antennas.

eess.SP↗

arXiv2022

Identification-Detection Group Testing Protocols for COVID-19 at High Prevalence

Group testing allows saving chemical reagents, analysis time, and costs, by testing pools of samples instead of individual samples. We introduce a class of group testing protocols with small dilution, suited to operate even at high prevalence ($5\%-10\%$), and maximizing the fraction of samples classified positive/negative within the first round of tests. Precisely, if the tested group has exactly one positive sample then the protocols identify it without further individual tests. The protocols also detect the presence of two or more positives in the group, in which case a second round could be applied to identify the positive individuals. With a prevalence of $5\%$ and maximum dilution 6, with 100 tests we classify 242 individuals, $92\%$ of them in one round and $8\%$ requiring a second individual test. In comparison, the Dorfman's scheme can test 229 individuals with 100 tests, with a second round for $18.5\%$ of the individuals.

physics.soc-ph↗

arXiv2022

Impact of Interference Subtraction on Grant-Free Multiple Access with Massive MIMO

The design of highly scalable multiple access schemes is a main challenge in the evolution towards future massive machine-type communications, where reliability and latency constraints must be ensured to a large number of uncoordinated devices. In this scenario, coded random access (CRA) schemes, where successive interference cancellation algorithms allow large improvements with respect to classical random access protocols, have recently attracted an increasing interest. Impressive performance can be potentially obtained by combining CRA with massive multiple input multiple output (MIMO). In this paper we provide an analysis of such schemes focusing on the effects of imperfect channel estimation on successive interference cancellation. Based on the analysis we then propose an innovative signal processing algorithm for CRA in massive MIMO systems.

cs.IT↗

arXiv2021

Analysis of Pointing Loss Effects in Deep Space Optical Links

Owing to the extremely narrow beams, a main issue in optical deep space communications is represented by miss-pointing errors, which may severely degrade the system performance and availability. In this paper, we address pointing losses in the case in which both the receiver and the transmitter are affected by angular errors. Pointing losses are evaluated through two approaches. The first approach is deterministic and only requires knowledge of a maximum angular error. The second approach requires knowledge of the angular error statistical distribution and tackles the problem from an outage probability viewpoint. These tools are then applied to analyze the impact of pointing losses in deep space optical links in which both terminals suffer from miss-pointing effects. The antenna gains are first optimized to maximize the effective system gain. The optimum antenna gains are then applied to evaluate maximum achievable ranges and to perform link design by means of optical link budgets.

eess.SP↗

arXiv2021

Short Codes for Quantum Channels with One Prevalent Pauli Error Type

One of the main problems in quantum information systems is the presence of errors due to noise, and for this reason quantum error-correcting codes (QECCs) play a key role. While most of the known codes are designed for correcting generic errors, i.e., errors represented by arbitrary combinations of Pauli X , Y and Z operators, in this paper we investigate the design of stabilizer QECC able to correct a given number eg of generic Pauli errors, plus eZ Pauli errors of a specified type, e.g., Z errors. These codes can be of interest when the quantum channel is asymmetric in that some types of error occur more frequently than others. We first derive a generalized quantum Hamming bound for such codes, then propose a design methodology based on syndrome assignments. For example, we found a [[9,1]] quantum error-correcting code able to correct up to one generic qubit error plus one Z error in arbitrary positions. This, according to the generalized quantum Hamming bound, is the shortest code with the specified error correction capability. Finally, we evaluate analytically the performance of the new codes over asymmetric channels.

quant-ph↗

arXiv2021

Optimum Detection of Defective Elements in Non-Adaptive Group Testing

We explore the problem of deriving a posteriori probabilities of being defective for the members of a population in the non-adaptive group testing framework. Both noiseless and noisy testing models are addressed. The technique, which relies of a trellis representation of the test constraints, can be applied efficiently to moderate-size populations. The complexity of the approach is discussed and numerical results on the false positive probability vs. false negative probability trade-off are presented.

cs.IT↗

arXiv2020

Piggybacking on Quantum Streams

This paper shows that it is possible to piggyback classical information on a stream of qubits protected by quantum error correcting codes. The piggyback channel can be created by introducing intentional errors corresponding to a controlled sequence of syndromes. These syndromes are further protected, when quantum noise is present, by classical error correcting codes according to a performance-delay trade-off. Classical information can thus be added and extracted at arbitrary epochs without consuming additional quantum resources and without disturbing the quantum stream.

quant-ph↗

arXiv2020

On the Distribution of an Arbitrary Subset of the Eigenvalues for some Finite Dimensional Random Matrices

We present some new results on the joint distribution of an arbitrary subset of the ordered eigenvalues of complex Wishart, double Wishart, and Gaussian hermitian random matrices of finite dimensions, using a tensor pseudo-determinant operator. Specifically, we derive compact expressions for the joint probability distribution function of the eigenvalues and the expectation of functions of the eigenvalues, including joint moments, for the case of both ordered and unordered eigenvalues.

math.ST↗

arXiv2019

Model Order Selection Based on Information Theoretic Criteria: Design of the Penalty

Information theoretic criteria (ITC) have been widely adopted in engineering and statistics for selecting, among an ordered set of candidate models, the one that better fits the observed sample data. The selected model minimizes a penalized likelihood metric, where the penalty is determined by the criterion adopted. While rules for choosing a penalty that guarantees a consistent estimate of the model order are known, theoretical tools for its design with finite samples have never been provided in a general setting. In this paper, we study model order selection for finite samples under a design perspective, focusing on the generalized information criterion (GIC), which embraces the most common ITC. The theory is general, and as case studies we consider: a) the problem of estimating the number of signals embedded in additive white Gaussian noise (AWGN) by using multiple sensors; b) model selection for the general linear model (GLM), which includes e.g. the problem of estimating the number of sinusoids in AWGN. The analysis reveals a trade-off between the probabilities of overestimating and underestimating the order of the model. We then propose to design the GIC penalty to minimize underestimation while keeping the overestimation probability below a specified level. For the considered problems, this method leads to analytical derivation of the optimal penalty for a given sample size. A performance comparison between the penalty optimized GIC and common AIC and BIC is provided, demonstrating the effectiveness of the proposed design strategy.

stat.ML↗

arXiv2019

On Oversampling-Based Signal Detection

The availability of inexpensive devices allows nowadays to implement cognitive radio functionalities in large-scale networks such as the internet-of-things and future mobile cellular systems. In this paper, we focus on wideband spectrum sensing in the presence of oversampling, i.e., the sampling frequency of a digital receiver is larger than the signal bandwidth, where signal detection must take into account the front-end impairments of low-cost devices. Based on the noise model of a software-defined radio dongle, we address the problem of robust signal detection in the presence of noise power uncertainty and non-flat noise power spectral density (PSD). In particular, we analyze the receiver operating characteristic of several detectors in the presence of such front-end impairments, to assess the performance attainable in a real-world scenario. We propose new frequency-domain detectors, some of which are proven to outperform previously proposed spectrum sensing techniques such as, e.g., eigenvalue-based tests. The study shows that the best performance is provided by a noise-uncertainty immune energy detector (ED) and, for the colored noise case, by tests that match the PSD of the receiver noise.

eess.SP↗

arXiv2019

On the LoRa Modulation for IoT: Waveform Properties and Spectral Analysis

An important modulation technique for Internet of Things (IoT) is the one proposed by the LoRa allianceTM. In this paper we analyze the M-ary LoRa modulation in the time and frequency domains. First, we provide the signal description in the time domain, and show that LoRa is a memoryless continuous phase modulation. The cross-correlation between the transmitted waveforms is determined, proving that LoRa can be considered approximately an orthogonal modulation only for large M. Then, we investigate the spectral characteristics of the signal modulated by random data, obtaining a closed-form expression of the spectrum in terms of Fresnel functions. Quite surprisingly, we found that LoRa has both continuous and discrete spectra, with the discrete spectrum containing exactly a fraction 1/M of the total signal power.

cs.NI↗

arXiv2018

Limits on Sparse Data Acquisition: RIC Analysis of Finite Gaussian Matrices

One of the key issues in the acquisition of sparse data by means of compressed sensing (CS) is the design of the measurement matrix. Gaussian matrices have been proven to be information-theoretically optimal in terms of minimizing the required number of measurements for sparse recovery. In this paper we provide a new approach for the analysis of the restricted isometry constant (RIC) of finite dimensional Gaussian measurement matrices. The proposed method relies on the exact distributions of the extreme eigenvalues for Wishart matrices. First, we derive the probability that the restricted isometry property is satisfied for a given sufficient recovery condition on the RIC, and propose a probabilistic framework to study both the symmetric and asymmetric RICs. Then, we analyze the recovery of compressible signals in noise through the statistical characterization of stability and robustness. The presented framework determines limits on various sparse recovery algorithms for finite size problems. In particular, it provides a tight lower bound on the maximum sparsity order of the acquired data allowing signal recovery with a given target probability. Also, we derive simple approximations for the RICs based on the Tracy-Widom distribution.

cs.IT↗

arXiv2017

Short Codes with Mismatched Channel State Information: A Case Study

The rising interest in applications requiring the transmission of small amounts of data has recently lead to the development of accurate performance bounds and of powerful channel codes for the transmission of short-data packets over the AWGN channel. Much less is known about the interaction between error control coding and channel estimation at short blocks when transmitting over channels with states (e.g., fading channels, phase-noise channels, etc...) for the setup where no a priori channel state information (CSI) is available at the transmitter and the receiver. In this paper, we use the mismatched-decoding framework to characterize the fundamental tradeoff occurring in the transmission of short data packet over an AWGN channel with unknown gain that stays constant over the packet. Our analysis for this simplified setup aims at showing the potential of mismatched decoding as a tool to design and analyze transmission strategies for short blocks. We focus on a pragmatic approach where the transmission frame contains a codeword as well as a preamble that is used to estimate the channel (the codeword symbols are not used for channel estimation). Achievability and converse bounds on the block error probability achievable by this approach are provided and compared with simulation results for schemes employing short low-density parity-check codes. Our bounds turn out to predict accurately the optimal trade-off between the preamble length and the redundancy introduced by the channel code.

cs.IT↗

arXiv2017

On the probability that all eigenvalues of Gaussian, Wishart, and double Wishart random matrices lie within an interval

We derive the probability that all eigenvalues of a random matrix $\bf M$ lie within an arbitrary interval $[a,b]$, $ψ(a,b)\triangleq\Pr\{a\leqλ_{\min}({\bf M}), λ_{\max}({\bf M})\leq b\}$, when $\bf M$ is a real or complex finite dimensional Wishart, double Wishart, or Gaussian symmetric/Hermitian matrix. We give efficient recursive formulas allowing the exact evaluation of $ψ(a,b)$ for Wishart matrices, even with large number of variates and degrees of freedom. We also prove that the probability that all eigenvalues are within the limiting spectral support (given by the Mar{č}enko-Pastur or the semicircle laws) tends for large dimensions to the universal values $0.6921$ and $0.9397$ for the real and complex cases, respectively. Applications include improved bounds for the probability that a Gaussian measurement matrix has a given restricted isometry constant in compressed sensing.

math.ST↗