108 research outputs found
Upper Bounds to the Performance of Cooperative Traffic Relaying in Wireless Linear Networks
Wireless networks with linear topology, where nodes generate their own traffic and relay other nodes' traffic, have attracted increasing attention. Indeed, they well represent sensor networks monitoring paths or streets, as well as multihop networks for videosurveillance of roads or vehicular traffic. We study the performance limits of such network systems when (i) the nodes' transmissions can reach receivers farther than one-hop distance from the sender, (ii) the transmitters cooperate in the data delivery, and (iii) interference due to concurrent transmissions is taken into account. By adopting an information-theoretic approach, we derive analytical bounds to the achievable data rate in both the cases where the nodes have full-duplex and half-duplex radios. The expressions we provide are mathematically tractable and allow the analysis of multihop networks with a large number of nodes. Our analysis highlights that increasing the number of coop- erating transmitters beyond two leads to a very limited gain in the achievable data rate. Also, for half-duplex radios, it indicates the existence of dominant network states, which have a major influence on the bound. It follows that efficient, yet simple, communication strategies can be designed by considering at most two cooperating transmitters and by letting half-duplex nodes operate according to the aforementioned dominant state
Toward an efficiently computable formula for the output statistics of MIMO block-fading channels
The information that can be conveyed through a wireless channel, with multiple-antenna equipped transmitter and receiver, crucially depends on the channel behavior as well as on the input structure. In this paper, we present very recent analytical results, concerning the probability density function (pdf) of the output of a single-user, multiple-antenna communication. The analysis is carried out under the assumption of an optimized input structure, and assuming Gaussian noise and block-fading. A further simplification of the output pdf expression presented in our last paper is derived, without the need for resorting to involved integration rules over unitary matrices. With respect to the former result, presented at the main track of this conference, the newly derived formula has the appealing feature of being numerically implementable with open access Matlab codes developed at MIT for the evaluation of zonal polynomial
Closed-form Output Statistics of MIMO Block-Fading Channels
The information that can be transmitted through a wireless channel, with
multiple-antenna equipped transmitter and receiver, is crucially influenced by
the channel behavior as well as by the structure of the input signal. We
characterize in closed form the probability density function (pdf) of the
output of MIMO block-fading channels, for an arbitrary SNR value. Our results
provide compact expressions for such output statistics, paving the way to a
more detailed analytical information-theoretic exploration of communications in
presence of block fading. The analysis is carried out assuming two different
structures for the input signal: the i.i.d. Gaussian distribution and a product
form that has been proved to be optimal for non-coherent communication, i.e.,
in absence of any channel state information. When the channel is fed by an
i.i.d. Gaussian input, we assume the Gramian of the channel matrix to be
unitarily invariant and derive the output statistics in both the noise-limited
and the interference-limited scenario, considering different fading
distributions. When the product-form input is adopted, we provide the
expressions of the output pdf as the relationship between the overall number of
antennas and the fading coherence length varies. We also highlight the relation
between our newly derived expressions and the results already available in the
literature, and, for some cases, we numerically compute the mutual information,
based on the proposed expression of the output statistics.Comment: 16 pages, 5 figure
Output Statistics of MIMO Channels with General Input Distribution
The information that can be conveyed through a wireless channel, with multiple-antenna equipped transmitter and receiver, crucially depends on the channel behavior as well as on the input structure. In this paper, we derive analytical results, concerning the probability density function (pdf) of the output of a single-user, multiple-antenna communication. The analysis is carried out under the assumption of an optimized input structure, and assuming Gaussian noise and a Rayleigh block-fading channel. Our analysis therefore provides a quite general and compact expression for the conditional output pdf. We also highlight the relation between such an expression and the results already available in the literature for some specific input structure
Information-theoretic Capacity of Clustered Random Networks
We analyze the capacity scaling laws of clustered ad hoc networks in which
nodes are distributed according to a doubly stochastic shot-noise Cox process.
We identify five different operational regimes, and for each regime we devise a
communication strategy that allows to achieve a throughput to within a
poly-logarithmic factor (in the number of nodes) of the maximum theoretical
capacity.Comment: 6 pages, in Proceedings of ISIT 201
Belief Dynamics in Social Networks: A Fluid-Based Analysis
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
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