The advent of Large Language Models (LLMs) and generative AI is fundamentally transforming information retrieval and processing on the Internet, bringing both great potential and significant concerns regarding content authenticity and reliability.This paper presents a novel quantitative approach to shed light on the complex information dynamics arising from the growing use of generative AI tools.Despite their significant impact on the digital ecosystem, these dynamics remain largely uncharted and poorly understood.We propose a stochastic model to characterize the generation, indexing, and dissemination of information in response to new topics.This scenario particularly challenges current LLMs, which often rely on real-time Retrieval-Augmented Generation (RAG) techniques to overcome their static knowledge limitations.Our findings suggest that the rapid pace of generative AI adoption, combined with increasing user reliance, can outpace human verification, escalating the risk of inaccurate information proliferation across digital resources.An in-depth analysis of Stack Exchange data confirms that high-quality answers inevitably require substantial time and human effort to emerge.This underscores the considerable risks associated with generating persuasive text in response to new questions and highlights the critical need for responsible development and deployment of future generative AI tools.

Motivated by the challenges of future 6G communications where terahertz (THz) frequencies, intelligent reflective surfaces (IRSs) and ultra-wideband (UWB) signals coexist, we analyze and propose a set of efficient techniques for configuring the IRS when the signal bandwidth is a significant fraction of the central frequency (up to 50%). To the best of our knowledge this is the first time that IRS configuration techniques are analyzed for such huge bandwidths. In our work we take into account for the channel model, the power spectral density of the signal reflected by the IRS and the network geometry. We evaluate the proposed solutions in terms of achievable rate and compare it against an upper bound we derived. Our results hint rules for designing IRS-aided communication systems and allow to draw conclusions on the trade-off between performance and complexity required for configuring the IRS.

We consider a constellation of low-earth-orbit (LEO) satellites connected to a handheld device on the ground. Due to the very large orbital speed, an effective handover strategy becomes of paramount importance. In particular, we study the benefits of soft handover in the uplink from the physical-layer point of view. We give a realistic model for both the ground-tosatellite and the inter-satellite links, following the 3GPP channel model for the former. We suppose that, during handover from a serving satellite to a target satellite, one of the two satellites forwards the received signal from the ground user to the other, thus acting as a relay. We quantify through simulations the loss of hard handover, compared to soft handover. For the latter, we test both amplify-and-forward (AF) and decode-and-forward (DF) relaying techniques and verify that, at least in the simulated conditions, DF does not repay, in terms of block error rate (BLER), the increase of complexity with respect to AF. Also, we study the effect of the LEO constellation size on the network BLER. Finally, we show that, with soft handover, the impact of misalignment on the inter-satellite link is severe, especially at optical frequencies.

We consider the optimization of a smart radio environment where meta-surfaces are employed to improve the performance of multiuser wireless networks working at sub-THz frequencies. Motivated by the extreme sparsity of the THz channel we propose to model each meta-surface as an electronically steerable reflector, by using only two parameters, regardless of its size. This assumption, although suboptimal in a general multiuser setup, allows for a significant complexity reduction when optimizing the environment and, despite its simplicity, is able to provide high communication rates. We derive a set of asymptotic results providing insight on the system behavior when both the number of antennas at the transmitter and the meta-surfaces area grow large. For the optimization we propose an algorithm based on the Newton-Raphson method and a simpler, yet effective, heuristic approach based on a map associating meta-surfaces and users. Through numerical results we provide insights on the system behavior and we assess the performance limits of the network in terms of supported users and spatial density of the meta-surfaces.

In this paper, we consider spatially coupled LDPC codes derived from protographs. In particular, we analyze the performance of the window decoder (WD), which allows reducing the complexity, the memory requirements, and the latency of the flood belief-propagation decoder. We show that the performance degradation of WD is due to the fact that it exploits a single decoding wave instead of two. This has effect both in the ideal case of infinite code length, where it may imply a threshold loss, and in the case of finite length, where it affects the slope of the BER curve in the waterfall region. We show how a forward-backward decoder can reduce such problems at the price of a limited increase of average complexity.

We investigate spatial patterns in mobile service consumption that emerge at national scale. Our investigation focuses on a representative case study, i.e., France, where we find that: (i) the demand for popular mobile services is fairly uniform across the whole country, and only a reduced set of peculiar services (mainly operating system updates and long-lived video streaming) yields geographic diversity; (ii) even for such distinguishing services, the spatial heterogeneity of demands is limited, and a small set of consumption behaviors is sufficient to characterize most of the mobile service usage across the country; (iii) the spatial distribution of these behaviors correlates well with the urbanization level, ultimately suggesting that the adoption of geographically-diverse mobile applications is linked to a dichotomy of cities and rural areas. We derive our results through the analysis of substantial measurement data collected by a major mobile network operator, leveraging an approach rooted in information theory that can be readily applied to other scenarios.

In this paper, we aim at answering the question "at what frequency should one sample individual human movements so that they can be reconstructed from the collected samples with minimum loss of information?". Our quest for a response unveils (i) seemingly universal spectral properties of human mobility, and (ii) a linear scaling law of the localization error with respect to the sampling interval. We conduct analyses using fine-grained GPS trajectories of 119 users worldwide. Our findings have potential applications in ubiquitous computing and mobile service design, in terms of energy efficiency, location-based service operations, active probing of subscribers' positions in mobile networks and trajectory data compression.

Mobile network operators can track subscribers via passive or active monitoring of device locations. The recorded trajectories offer an unprecedented outlook on the activities of large user populations, which enables developing new networking solutions and services, and scaling up studies across research disciplines. Yet, the disclosure of individual trajectories raises significant privacy concerns: thus, these data are often protected by restrictive non-disclosure agreements that limit their availability and impede potential usages. In this paper, we contribute to the development of technical solutions to the problem of privacy-preserving publishing of spatiotemporal trajectories of mobile subscribers. We propose an algorithm that generalizes the data so that they satisfy-anonymity, an original privacy criterion that thwarts attacks on trajectories. Evaluations with real-world datasets demonstrate that our algorithm attains its objective while retaining a substantial level of accuracy in the data. Our work is a step forward in the direction of open, privacy-preserving datasets of spatiotemporal trajectories.

This paper presents the first systematic investigation of the potential performance gains for crowd work systems, deriving from available information at the requester about individual worker reputation. In particular, we first formalize the optimal task assignment problem when workers' reputation estimates are available, as the maximization of a monotone (submodular) function subject to Matroid constraints. Then, being the optimal problem NP-hard, we propose a simple but efficient greedy heuristic task allocation algorithm. We also propose a simple “maximum a-posteriori” decision rule and a decision algorithm based on message passing. Finally, we test and compare different solutions, showing that system performance can greatly benefit from information about workers' reputation. Our main findings are that: i) even largely inaccurate estimates of workers' reputation can be effectively exploited in the task assignment to greatly improve system performance; ii) the performance of the maximum a-posteriori decision rule quickly degrades as worker reputation estimates become inaccurate; iii) when workers' reputation estimates are significantly inaccurate, the best performance can be obtained by combining our proposed task assignment algorithm with the message-passing decision algorithm.

This paper presents the first systematic investigation of the potential performance gains for crowdsourcing systems, deriving from available information at the requester about individual worker earnestness (reputation). In particular, we first formalize the optimal task assignment problem when workers' reputation estimates are available, as the maximization of a monotone (submodular) function subject to Matroid constraints. Then, being the optimal problem NP-hard, we propose a simple but efficient greedy heuristic task allocation algorithm. We also propose a simple “maximum a-posteriori“ decision rule. Finally, we test and compare different solutions, showing that system performance can greatly benefit from information about workers' reputation. Our main findings are that: i) even largely inaccurate estimates of workers' reputation can be effectively exploited in the task assignment to greatly improve system performance; ii) the performance of the maximum a-posteriori decision rule quickly degrades as worker reputation estimates become inaccurate; iii) when workers' reputation estimates are significantly inaccurate, the best performance can be obtained by combining our proposed task assignment algorithm with the LRA decision rule introduced in the literature.

We present bounds and a closed-form high-SNR expression for the capacity of multiple-antenna systems affected by Wiener phase noise. Our results are developed for the scenario where a single oscillator drives all the radio-frequency circuitries at each transceiver (common oscillator setup), the input signal is subject to a peak-power constraint, and the channel matrix is deterministic. This scenario is relevant for line-of-sight multiple-antenna microwave backhaul links with sufficiently small antenna spacing at the transceivers. For the 2×2 multiple-antenna case, for a Wiener phase-noise process with standard deviation equal to 6°, and at the medium/high SNR values at which microwave backhaul links operate, the upper bound reported in the paper exhibits a 3dB gap from a lower bound obtained using 64-QAM. Furthermore, in this SNR regime the closed-form high-SNR expression is shown to be accurate.

We analyze the achievable data rate of cooperative relaying strategies in networks where nodes operate in half-duplex mode. Nodes have to deliver their data to a gateway, at a certain rate, and may have limited energy capabilities, as in the case of energy-harvesting communication networks. Both the requested data rate and the available energy capabilities may vary from node to node. Under such constraints, we take an information-theoretic approach and derive cut-set upper bounds to the achievable rate. Furthermore, we devise two kinds of communication strategies, each aiming at a different objective. The former ensures a fair rate allocation to the network nodes, but it neglects their energy constraints. The latter does consider energy constraints by meeting the requirements on the average power consumption at each node and by providing fairness in the data rate allocation. We show the performance of the aforementioned communication strategies, highlighting their effectiveness and providing useful insights on the system behavior.

We compute the optimal communication rate achieved by the nodes of a wireless multihop network with arbitrary topology. The network nodes operate in half-duplex mode and generate information that has to be delivered to a gateway node, possibly through a decode-and-forward relaying strategy. Nodes may make use of multiuser processing, thus transmissions from multiple nodes toward the same receiver are allowed. Additionally, nodes may be energy-constrained, as in the case of battery-powered or energy-harvesting communication networks. In such a scenario, we define the possible (and meaningful) network operational states. Then, by solving a linear optimization problem, we select the most efficient network states and for how long the network should work in each of them. More specifically, the resulting communication strategy maximizes the data rate achievable by the network while meeting the constraints that may exist on the node energy consumption. The results we present show how our approach can be effectively used for an optimal design and usage of wireless networks, as well as under which conditions multiuser processing and long-distance communication between nodes are most beneficial.

We consider a multiple-input multiple-output (MIMO) AWGN channel affected by phase noise. Focusing on the 2 × 2 case, we show that no MIMO multiplexing gain is to be expected when the phase-noise processes at each antenna are independent, memoryless in time, and with uniform marginal distribution over [0, 2π] (strong phase noise), and when the transmit signal is isotropically distributed on the real plane. The scenario of independent phase-noise processes across antennas is relevant for microwave backhaul links operating in the 20-40 GHz range.

In this paper, we derive a phase-noise estimator for MIMO systems affected by independent phase noise at each antenna. The proposed phase-noise estimator employs the expectation-maximization algorithm and can incorporate channel decoding. The main feature of the proposed estimator lies in the fact that it estimates separately phase-noise samples at the transmitter and at the receiver, instead of estimating, as it is typical in single-antenna case, the sum of the samples at the two sides. Simulation results show that the proposed estimator allows obtaining a very good performance at an affordable complexity.

This paper deals with the problem of stabilizing an unstable system through networked control over the wireless medium. In such a situation a remote sensor communicates the measurements to the system controller through a noisy channel. In particular, in the AWGN scenario, we show that protograph-based LDPC convolutional codes achieve anytime reliability and we also derive a lower bound to the signal-to-noise ratio required to stabilize the system. Moreover, on the Rayleigh-fading channel, we show by simulations that resorting to multiple sensors reduces the SNR required for system stabilization.

This paper deals with full-diversity schemes for MIMO systems in a slowly-varying fading environment. We consider LDPC codes expressly designed for block-fading channels (rootcheck LDPC) and we couple them with spatial multiplexing, to show that they achieve diversity gain, unlike traditional LDPC codes. At the receiver, we consider an iterative turbo-like receiver, both with the optimal demodulator and a suboptimal one, based on linear MMSE filtering. To improve the performance of the latter one, a power unbalance between transmit antennas is introduced. Simulation results and semianalytical techniques like EXIT charts show that our optimized schemes do achieve full diversity.

This paper enhances earlier work on random selection and forwarding, which is a probabilistic forwarding protocol for wireless relay networks. We have extended the system model to account for more realistic scenarios and we have applied the framework to the conventional first-in first-out forwarding technique, which we use as a reference for comparison. Most importantly, we have analyzed the asymptotic behavior of the packet erasure probability and we have derived expressions which shed more light on the interplay between the various network parameters and their impact on the packet erasure probability.

In this paper, we propose an iterative SIC receiver architecture with pilot- and data-based channel estimation for efficient decoding of non-orthogonal superimposed signals. The non-orthogonal superposition concept on top of OFDMA is a promising technique to improve cell spectral efficiency. In the cellular case, where users with significant path loss are superimposed by an intelligent scheduler, the SIC multi-user receiver scheme is well adapted for user signal separation. Based on the proposed receiver, we show the performance by means of multi-link link-level simulations in a realistic OFDMA uplink system including channel estimation based on real pilot patterns.

The pragmatic approach to coded continuous-phase modulation (CPM) is proposed as a capacity-achieving low-complexity alternative to the serially concatenated CPM (SC-CPM) coding scheme. In this paper, we first perform a selection of the best spectrally efficient CPM modulations to be embedded into SC-CPM schemes. Then, we consider the pragmatic capacity (a.k.a. BICM capacity) of CPM modulations and optimize it through a careful design of the mapping between input bits and CPM waveforms. The so obtained schemes are cascaded with an outer serially concatenated convolutional code to form a pragmatic coded-modulation system. The resulting schemes exhibit performance very close to the CPM capacity without requiring iterations between the outer decoder and the CPM demodulator. As a result, the receiver exhibits reduced complexity and increased flexibility due to the separation of the demodulation and decoding functions.

This paper deals with LT and Raptor codes used on a noiseless channel, as it is the case for the BEC or the AWGN channel with high SNR. The performance measure for such family of codes is the efficiency, i.e., the average amount of redundancy needed to decode the information bits. We consider the new class of graph-based LT and Raptor codes, we analyze their efficiency and we show that the optimal degree distribution of the LT code depends on the rate of the precoder.

The paper extends the pragmatic approach to coded continuous-phase modulation (CPM). It first proposes an optimization of the CPM capacity for given complexity and bandwidth efficiency. Then, the best CPM schemes are embedded into a pragmatic coded-modulation scheme, whose pragmatic capacity (a.k.a. BICM capacity) is maximized through a careful design of the mapping between input bits and CPM waveforms. The so obtained CPM schemes show a pragmatic capacity very close to the CPM capacity. An outer binary serially-concatenated convolutional code, cascaded with the CPM modulator through an interleaver, yields performance close to the pragmatic (and so to the CPM) capacity without requiring iterations between outer code and CPM modulator.

This paper deals with precode-only (PCO) Raptor codes and turbo fountain codes used on a noiseless channel, as it is the case for the BEC or the AWGN channel with high SNR. The performance measure for such family of codes is the efficiency, i.e., the amount of redundancy needed to decode the information bits. Following a previous paper, we give an exact expression for the average efficiency of maximum-likelihood (ML) decoded Hamming codes and maximal-length codes. Moreover, we give an expression of the variance of the efficiency. Finally, we improve the bound on the efficiency of turbo fountain codes, which are iteratively decoded.

The analysis and design of spacetime codes for correlated fading channels when the diversity gain is large enough is considered. We derive a simple form for a distance metric that characterizes the code performance in the presence of transmit correlation, and propose some design criteria to build good space time trellis codes (STTCs) for correlated channels. For the case of two transmit antennas, we show that in strongly correlated channels, performance is governed by the constellation that results from the sum of the constellations associated with the transmit antennas. This suggests the use of new constellations to design better codes for correlated channels. The design criteria are then extended to any number of transmit antennas. Based on these criteria, we derive new STTCs for two and three transmit antennas that perform much better in correlated channels than the STTC optimized for the independent and identically distributed case. We also consider set partitioning applied to the sum constellation as a simple technique to design good codes for correlated channels. The codes derived show performance close to the codes found by an exhaustive search. Finally, we consider antenna selection as an alternative to build good codes for more than two antennas in fading-correlated scenarios.

In this paper we propose a technique to implement in a parallel fashion a turbo decoder based on an arbitrary permutation, and to expand its interleaver in order to produce a family of prunable S-random interleavers suitable for parallel implementations. We show that the spread properties of the obtained interleavers are almost optimal and we prove by simulation that they are very competitive in terms of error floor performance. A few details on the decoder architecture are also provided.

In a previous paper as presented by Tarable et al. (2004), the authors introduced the concept of mapping functions as a tool to cope with the problem of collision-free memory mappings in turbo and LDPC parallel decoder implementations. In this paper, we address some implementation issues of the original solution, define a dual problem, which can be of high interest for practical implementations, and give the generalization of mapping functions to N > 2 parallel decoders.

We deal with the design of interleavers in a coded code-division multiple-access (CDMA) scenario, where at the receiver an iterative turbo-like structure to perform multiuser detection is employed. The choice of the interleavers affects both the maximum-likelihood (ML) performance and the impact of the suboptimality of the iterative receiver. First, heuristic criteria of goodness for a set of interleavers, each assigned to a given active user, are introduced and motivated. One of these criteria is based on the intersection between the equivalent codes seen after the interleavers for each user pair. The design rules are valid for any kind of channel code. In particular, when the channel code used by every user is a terminated convolutional code, a very simple design rule, in the subset of congruential interleavers, is specified. The suitability of an interleaver set to iterative decoding is also treated. The analysis leads to a design rule which is shown to have great importance on the performance of a turbo-like receiver. Numerical results assess the validity of the derived design rules by showing that, for iterative multiuser receivers and reasonable block lengths, the suitability to iterative decoding is more important than the performance optimization.

In this paper, after a description of the principles of iterative (turbo) multiuser detection for CDMA systems, a new structure, based on a linear user separator, is introduced and analyzed. The new user separator processes the matched filter outputs according to a minimum mean-square-error (MMSE) criterion for the first few iterations, while it bypasses the MMSE filter when the interferers' bits are known with some reliability. This new receiver is tested by simulation and compared with other receivers previously introduced in literature. Also, a way of studying and designing iterative multiuser receivers is given by adapting the method of EXtrinsic Information Transfer (EXIT) charts. With the EXIT charts, the receiver performance (in an information-theoretic sense) can be evaluated as it evolves along the iterations. Thus, the receiver threshold can be reliably estimated.

The main problem of space-time trellis codes is constituted by their complexity, which grows exponentially with the number of transmit antennas. To avoid this shortcoming, one can think to a suboptimum decoder in which a simplified metric, together with a preliminary filtering step, is used. In this paper, we develop this idea and give some possible choices for the filter design. These different choices are compared with one another by means of analytical tools and simulations.

For high-data-rate applications, the implementation of iterative turbo-like decoders requires the use of parallel architectures posing some collision-free constraints to the reading/writing process from/into the memory. This consideration applies to the two main classes of turbo-like codes, i.e., turbo codes and low-density parity-check (LDPC) codes. Contrary to the literature belief, we prove in this paper that there is no need for an ad hoc code design to meet the parallelism requirement, because, for any code and any choice of the scheduling of the reading/writing operations, there is a suitable mapping of the variables in the memory that grants a collision-free access. The proof is constructive, i.e., it gives an algorithm that obtains the desired collision-free mapping. The algorithm is applied to two simple examples, one for turbo codes and one for LDPC codes, to illustrate how the algorithm works.

Sstarting from recent results on MIMO channels, we design a new transceiver for a code division multiaccess scenario with multiantenna transmitter and receiver. The proposed structure is based on a combination of trellis modulation, turbo codes and differential unitary space-time modulation.

A new suboptimal turbo receiver for coded CDMA is presented. The user-separating front-end of this receiver has been thought of as the extension of linear multiuser detectors to an iterative structure. The complexity of this receiver is shown to be O(K), where K is the number of users. Simulations show that, for sufficiently high signal-to-noise ratios, the linear-US receiver tends to single-user performance.