143 research outputs found

    Anytime Reliable LDPC Convolutional Codes for Networked Control over Wireless Channel

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    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 allows to achieve a diversity gain.Comment: 5 pages, 3 figures, submitted to IEEE International Symposium on Information Theory 2013 (ISIT 2013

    Capacity bounds for MIMO microwave backhaul links affected by phase noise

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    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 by 2 multiple-antenna case, for a Wiener phase-noise process with standard deviation equal to 6 degrees, and at the medium/high SNR values at which microwave backhaul links operate, the upper bound reported in the paper exhibits a 3 dB 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.Comment: 10 pages, 2 figures, to appear in IEEE Transactions on Communication

    Capacity-achieving CPM schemes

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    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.Comment: Submitted to IEEE Transactions on Information Theor

    Belief Dynamics in Social Networks: A Fluid-Based Analysis

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    The advent and proliferation of social media have led to the development of mathematical models describing the evolution of beliefs/opinions in an ecosystem composed of socially interacting users. The goal is to gain insights into collective dominant social beliefs and into the impact of different components of the system, such as users' interactions, while being able to predict users' opinions. Following this thread, in this paper we consider a fairly general dynamical model of social interactions, which captures all the main features exhibited by a social system. For such model, by embracing a mean-field approach, we derive a diffusion differential equation that represents asymptotic belief dynamics, as the number of users grows large. We then analyze the steady-state behavior as well as the time dependent (transient) behavior of the system. In particular, for the steady-state distribution, we obtain simple closed-form expressions for a relevant class of systems, while we propose efficient semi-analytical techniques in the most general cases. At last, we develop an efficient semi-analytical method to analyze the dynamics of the users' belief over time, which can be applied to a remarkably large class of systems.Comment: submitted to IEEE TNS

    On the multiplexing gain of MIMO Microwave backhaul links affected by Phase Noise

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    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

    A Formal Framework for Modeling Trust and Reputation in Collective Adaptive Systems

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    Trust and reputation models for distributed, collaborative systems have been studied and applied in several domains, in order to stimulate cooperation while preventing selfish and malicious behaviors. Nonetheless, such models have received less attention in the process of specifying and analyzing formally the functionalities of the systems mentioned above. The objective of this paper is to define a process algebraic framework for the modeling of systems that use (i) trust and reputation to govern the interactions among nodes, and (ii) communication models characterized by a high level of adaptiveness and flexibility. Hence, we propose a formalism for verifying, through model checking techniques, the robustness of these systems with respect to the typical attacks conducted against webs of trust.Comment: In Proceedings FORECAST 2016, arXiv:1607.0200
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