Living at the Edge: A Large Deviations Approach to the Outage MIMO Capacity

Using a large deviations approach we calculate the probability distribution of the mutual information of MIMO channels in the limit of large antenna numbers. In contrast to previous methods that only focused at the distribution close to its mean (thus obtaining an asymptotically Gaussian distribution), we calculate the full distribution, including its tails which strongly deviate from the Gaussian behavior near the mean. The resulting distribution interpolates seamlessly between the Gaussian approximation for rates $R$ close to the ergodic value of the mutual information and the approach of Zheng and Tse for large signal to noise ratios $\rho$. This calculation provides us with a tool to obtain outage probabilities analytically at any point in the $(R, \rho, N)$ parameter space, as long as the number of antennas $N$ is not too small. In addition, this method also yields the probability distribution of eigenvalues constrained in the subspace where the mutual information per antenna is fixed to $R$ for a given $\rho$. Quite remarkably, this eigenvalue density is of the form of the Marcenko-Pastur distribution with square-root singularities, and it depends on the values of $R$ and $\rho$.Comment: Accepted for publication, IEEE Transactions on Information Theory (2010). Part of this work appears in the Proc. IEEE Information Theory Workshop, June 2009, Volos, Greec

Closed-Form Density of States and Localization Length for a Non-Hermitian Disordered System

We calculate the Lyapunov exponent for the non-Hermitian Zakharov-Shabat eigenvalue problem corresponding to the attractive non-linear Schroedinger equation with a Gaussian random pulse as initial value function. Using an extension of the Thouless formula to non-Hermitian random operators, we calculate the corresponding average density of states. We analyze two cases, one with circularly symmetric complex Gaussian pulses and the other with real Gaussian pulses. We discuss the implications in the context of the information transmission through non-linear optical fibers.Comment: 5 pages, 1 figur

Entrepreneurial sons, patriarchy and the Colonels' experiment in Thessaly, rural Greece

Existing studies within the field of institutional entrepreneurship explore how entrepreneurs influence change in economic institutions. This paper turns the attention of scholarly inquiry on the antecedents of deinstitutionalization and more specifically, the influence of entrepreneurship in shaping social institutions such as patriarchy. The paper draws from the findings of ethnographic work in two Greek lowland village communities during the military Dictatorship (1967–1974). Paradoxically this era associated with the spread of mechanization, cheap credit, revaluation of labour and clear means-ends relations, signalled entrepreneurial sons’ individuated dissent and activism who were now able to question the Patriarch’s authority, recognize opportunities and act as unintentional agents of deinstitutionalization. A ‘different’ model of institutional change is presented here, where politics intersects with entrepreneurs, in changing social institutions. This model discusses the external drivers of institutional atrophy and how handling dissensus (and its varieties over historical time) is instrumental in enabling institutional entrepreneurship

M2-Branes and Fano 3-folds

A class of supersymmetric gauge theories arising from M2-branes probing Calabi-Yau 4-folds which are cones over smooth toric Fano 3-folds is investigated. For each model, the toric data of the mesonic moduli space is derived using the forward algorithm. The generators of the mesonic moduli space are determined using Hilbert series. The spectrum of scaling dimensions for chiral operators is computed.Comment: 128 pages, 39 figures, 42 table

Distribution of MIMO Mutual Information: a Large Deviations Approach

International audienceUsing a large deviations approach we calculate the probability distribution of the mutual information of MIMO channels in the limit of large antenna numbers. In contrast to previous methods that only focused to the distribution close to its most probable value, thus obtaining an asymptotically Gaussian distribution, we calculate the full distribution including its tails, which behave quite differently from the bulk of the distribution. Our resulting probability distribution seamlessly interpolates between the Gaussian approximation for rates R close to the ergodic value of the mutual information and the approach of Zheng and Tse, valid for large signal to noise ratios ρ. This provides us with a tool to analytically calculate outage probabilities at any point in the (R, ρ,N) parameter space, as long as the number of antennas N is not too small. In addition, this method also yields the probability distribution of eigenvalues constrained in the subspace where the mutual information per antenna is fixed to R for a given ρ. Quite remarkably, this eigenvalue density is of the form of the Marcenko-Pastur distribution with square-root singularities

Distribution of MIMO Mutual Information: a Large Deviations Approach

International audienceUsing a large deviations approach we calculate the probability distribution of the mutual information of MIMO channels in the limit of large antenna numbers. In contrast to previous methods that only focused to the distribution close to its most probable value, thus obtaining an asymptotically Gaussian distribution, we calculate the full distribution including its tails, which behave quite differently from the bulk of the distribution. Our resulting probability distribution seamlessly interpolates between the Gaussian approximation for rates R close to the ergodic value of the mutual information and the approach of Zheng and Tse, valid for large signal to noise ratios ρ. This provides us with a tool to analytically calculate outage probabilities at any point in the (R, ρ,N) parameter space, as long as the number of antennas N is not too small. In addition, this method also yields the probability distribution of eigenvalues constrained in the subspace where the mutual information per antenna is fixed to R for a given ρ. Quite remarkably, this eigenvalue density is of the form of the Marcenko-Pastur distribution with square-root singularities

Distribution of MIMO Mutual Information: A Large Deviations Approach

Using a large deviations approach we calculate the probability distribution of the mutual information of MIMO channels in the limit of large antenna numbers. In contrast to previous methods that only focused to the distribution close to its most probable value, thus obtaining an asymptotically Gaussian distribution, we calculate the full distribution including its tails, which behave quite differently from the bulk of the distribution. Our resulting probability distribution seamlessly interpolates between the Gaussian approximation for rates R close to the ergodic value of the mutual information and the approach of Zheng and Tse [1], valid for large signal to noise ratios rho. This provides us with a tool to analytically calculate outage probabilities at any point in the (R, rho, N) parameter space, as long as the number of antennas N is not too small. In addition, this method also yields the probability distribution of eigenvalues constrained in the subspace where the mutual information per antenna is fixed to R for a given rho. Quite remarkably, this eigenvalue density is of the form of the Marcenko-Pastur distribution with square-root singularities