Erwin Riegler

On the achievability of interference alignment in the K-user constant MIMO interference channel

Interference alignment in the K-user MIMO interference channel with constant channel coefficients is considered. A novel constructive method for finding the interference alignment solution is proposed for the case where the number of transmit antennas equals the number of receive antennas (NT = NR = N), the number of transmitter-receiver pairs equals K = N + 1, and all interference alignment multiplexing gains are one. The core of the method consists of solving an eigenvalue problem that incorporates the channel matrices of all interfering links. This procedure provides insight into the feasibility of signal vector spaces alignment schemes in finite dimensional MIMO interference channels.

Topological string amplitudes, complete intersection Calabi-Yau spaces and threshold corrections

We present the most complete list of mirror pairs of Calabi-Yau complete intersections in toric ambient varieties and develop the methods to solve the topological string and to calculate higher genus amplitudes on these compact Calabi-Yau spaces. These symplectic invariants are used to remove redundancies in examples. The construction of the B-model propagators leads to compatibility conditions, which constrain multi-parameter mirror maps. For K3 fibered Calabi-Yau spaces without reducible fibers we find closed formulas for all genus contributions in the fiber direction from the geometry of the fibration. If the heterotic dual to this geometry is known, the higher genus invariants can be identified with the degeneracies of BPS states contributing to gravitational threshold corrections and all genus checks on string duality in the perturbative regime are accomplished. We find, however, that the BPS degeneracies do not uniquely fix the non-perturbative completion of the heterotic string. For these geometries we can write the topological partition function in terms of the Donaldson-Thomas invariants and we perform a non-trivial check of S-duality in topological strings. We further investigate transitions via collapsing D5 del Pezzo surfaces and the occurrence of free 2 quotients that lead to a new class of heterotic duals.

On the Capacity of Large-MIMO Block-Fading Channels

We characterize the capacity of Rayleigh block-fading multiple-input multiple-output (MIMO) channels in the noncoherent setting where transmitter and receiver have no a priori knowledge of the realizations of the fading channel. We prove that unitary space-time modulation (USTM) is not capacity-achieving in the high signal-to-noise ratio (SNR) regime when the total number of antennas exceeds the coherence time of the fading channel (expressed in multiples of the symbol duration), a situation that is relevant for MIMO systems with large antenna arrays (large-MIMO systems). This result settles a conjecture by Zheng & Tse (2002) in the affirmative. The capacity-achieving input signal, which we refer to as Beta-variate space-time modulation (BSTM), turns out to be the product of a unitary isotropically distributed random matrix, and a diagonal matrix whose nonzero entries are distributed as the square-root of the eigenvalues of a Beta-distributed random matrix of appropriate size. Numerical results illustrate that using BSTM instead of USTM in large-MIMO systems yields a rate gain as large as 13% for SNR values of practical interest.

Fixed points of generalized approximate message passing with arbitrary matrices

The estimation of a random vector with independent components passed through a linear transform followed by a componentwise (possibly nonlinear) output map arises in a range of applications. Approximate message passing (AMP) methods, based on Gaussian approximations of loopy belief propagation, have recently attracted considerable attention for such problems. For large random transforms, these methods exhibit fast convergence and admit precise analytic characterizations with testable conditions for optimality, even for certain non-convex problem instances. However, the behavior of AMP under general transforms is not fully understood. In this paper, we consider the generalized AMP (GAMP) algorithm and relate the method to more common optimization techniques. This analysis enables a precise characterization of the GAMP algorithm fixed-points that applies to arbitrary transforms. In particular, we show that the fixed points of the so-called max-sum GAMP algorithm for MAP estimation are critical points of a constrained maximization of the posterior density. The fixed-points of the sum-product GAMP algorithm for estimation of the posterior marginals can be interpreted as critical points of a certain mean-field variational optimization.

Merging Belief Propagation and the Mean Field Approximation: A Free Energy Approach

We present a joint message passing approach that combines belief propagation and the mean field approximation. Our analysis is based on the region-based free energy approximation method proposed by Yedidia et al. We show that the message passing fixed-point equations obtained with this combination correspond to stationary points of a constrained region-based free energy approximation. Moreover, we present a convergent implementation of these message passing fixed-point equations provided that the underlying factor graph fulfills certain technical conditions. In addition, we show how to include hard constraints in the part of the factor graph corresponding to belief propagation. Finally, we demonstrate an application of our method to iterative channel estimation and decoding in an orthogonal frequency division multiplexing system.

Variational Message-Passing for Joint Channel Estimation and Decoding in MIMO-OFDM

In this contribution, a multi-user receiver for M- QAM MIMO-OFDM operating in time-varying and frequency-selective channels is derived. The proposed architecture jointly performs semi-blind estimation of the channel weights and noise inverse variance, serial interference cancellation and decoding in an iterative manner. The scheme relies on a variational message-passing approach, which enables a joint design of all these functionalities or blocks but the last one. Decoding is performed using the sum-product algorithm. This is in contrast to nowadays proposed approaches in which all these blocks are designed and optimized individually. Simulation results show that the proposed receiver outperforms in coded bit-error-rate a state-of-the- art iterative receiver of same complexity, in which all blocks are designed independently. Joint block design and, as a result, the fact that the uncertainty in the channel estimation is accounted for in the proposed receiver explain this better performance.

On the Ergodic Capacity of Correlated Rician Fading MIMO Channels With Interference

An asymptotic approach to derive the ergodic capacity achieving covariance matrix for a multiple-input multiple-output (MIMO) channel is presented. The method is applicable to MIMO channels affected by separately correlated Rician fading and co-channel interference. It is assumed that the number of transmit, receive and interfering antennas grows asymptotically while their ratios, as well as the SNR and the SIR, approach finite constants. Nevertheless, it is shown that the asymptotic results represent an accurate approximation in the case of a finitely many antennas and can be used to derive the ergodic channel capacity. This is accomplished by using an iterative power allocation algorithm based on a water-filling approach. The convergence of a similar algorithm (nicknamed frozen water-filling) was conjectured in a work by Dumont Here, we show that, in the Rayleigh case, the frozen water-filling algorithm may not converge while, in those cases, our proposed algorithm converges. Finally, numerical results are included in order to assess the accuracy of the asymptotic method proposed, which is compared to equivalent results obtained via Monte-Carlo simulations.

Toric complete intersections and weighted projective space

Abstract It has been shown by Batyrev and Borisov that nef partitions of reflexive polyhedra can be used to construct mirror pairs of complete intersection Calabi–Yau manifolds in toric ambient spaces. We construct a number of such spaces and compute their cohomological data. We also discuss the relation of our results to complete intersections in weighted projective spaces and try to recover them as special cases of the toric construction. As compared to hypersurfaces, codimension two more than doubles the number of spectra with h 11 =1. Altogether we find 87 new (mirror pairs of) Hodge data, mainly with h 11 ≤4.

Soft-Heuristic Detectors for Large MIMO Systems

We propose low-complexity detectors for large MIMO systems with BPSK or QAM constellations. These detectors work at the bit level and consist of three stages. In the first stage, maximum likelihood decisions on certain bits are made in an efficient way. In the second stage, soft values for the remaining bits are calculated. In the third stage, these remaining bits are detected by means of a heuristic programming method for high-dimensional optimization that uses the soft values (“soft-heuristic” algorithm). We propose two soft-heuristic algorithms with different performance and complexity. We also consider a feedback of the results of the third stage for computing improved soft values in the second stage. Simulation results demonstrate that, for large MIMO systems, our detectors can outperform state-of-the-art detectors based on nulling and canceling, semidefinite relaxation, and likelihood ascent search.

Message-passing algorithms for channel estimation and decoding using approximate inference

We design iterative receiver schemes for a generic communication system by treating channel estimation and information decoding as an inference problem in graphical models. We introduce a recently proposed inference framework that combines belief propagation (BP) and the mean field (MF) approximation and includes these algorithms as special cases. We also show that the expectation propagation and expectation maximization (EM) algorithms can be embedded in the BP-MF framework with slight modifications. By applying the considered inference algorithms to our probabilistic model, we derive four different message-passing receiver schemes. Our numerical evaluation in a wireless scenario demonstrates that the receiver based on the BP-MF framework and its variant based on BP-EM yield the best compromise between performance, computational complexity and numerical stability among all candidate algorithms.