Paulo G. Normando

Performance of Joint Antenna and User Selection Schemes for Interference Alignment in MIMO Interference Channels

In multiuser MIMO systems, the transmitter can select a subset of antennas and/or users which have good channel conditions to maximize the system throughput using various selection criteria. Furthermore, the Interference Alignment (IA) method, which is based on the concept of precoding, can provide interference free dimensions. It offers different trade-offs between complexity and performance. The basic idea of Interference Alignment consists in precoding the transmitted signals such that they are aligned at the receiver where they constitute interference, while at the same time disjointed from the desired signal. We analyze the performance of antenna selection and multiuser diversity together in order to allow opportunistic IA using chordal and Fubini-Study distances. Analyses and simulations verify the behavior of the proposed scheme.

Microstructure identification via detrended fluctuation analysis of ultrasound signals.

We describe an algorithm for simulating ultrasound propagation in random one-dimensional media, mimicking different microstructures by choosing physical properties such as domain sizes and mass densities from probability distributions. By combining a detrended fluctuation analysis (DFA) of the simulated ultrasound signals with tools from the pattern-recognition literature, we build a Gaussian classifier which is able to associate each ultrasound signal with its corresponding microstructure with a very high success rate. Furthermore, we also show that DFA data can be used to train a multilayer perceptron which estimates numerical values of physical properties associated with distinct microstructures.

CHARACTERIZATION OF CAST IRON MICROSTRUCTURE THROUGH THE STATISTICAL FLUCTUATION AND FRACTAL ANALYSES OF ULTRASONIC BACKSCATTERED SIGNALS

This work aims to identify the different microstructures presented by cast iron, namely, lamellar, vermicular and spheroidal microstructures, through the statistical fluctuation and fractal analyses of backscattered ultrasonic signals. The signals were obtained with a broadband direct contact ultrasonic probe with a central frequency of 5 MHz. The statistical fluctuations of the ultrasonic signals were analyzed using Hurst and detrended‐fluctuation analyses (DFA), and the fractal analyses were carried out by applying the minimal cover and box‐counting techniques to the signals. The curves obtained for the statistical fluctuations and fractal analyses, as function of time window, were processed by using two pattern classification techniques, namely, principal‐component analysis (PCA) and Karhunen‐Loeve expansion. For the Karhunen‐Loeve expansion, an approximately 100% success rate has been reached for the classification of the different microstructures, for the training and the testing sets of events. The ...

Transmission Strategy for Interference Alignment in a System-Level Perspective

The paper builds up on the idea of separating, in the time dimension, between conventional uncoordinated MIMO and IA transmission. The former usually utilizes all available dimensions (antennas) to send useful information, while the latter mitigates inter-cell interference. Due to the multitude of users in cellular networks, the transmission schemes are suitable for different groups of users. Therefore, in order to take advantage of both schemes, the users are classified into two groups: one with those users that supposedly benefit from cooperation and the other with those that should not cooperate. The proposed method for grouping the users has the advantage of being based on a simple decision metric, which avoids having to calculate precoders for all different possible combinations. Since each group must apply the proper transmission scheme, a fraction of the temporal resources is dedicated to each type of transmission. An automatic reservation of the temporal resources and an adaptive adjustment of the grouping threshold for each user, which avoids having to empirically determine a single threshold, are also proposed. These proposed mechanisms are shown to provide performance gains of up to 30% over the conventional transmissions.

Performance of interference alignment techniques within CoMP-like systems

Interference Alignment (IA) is a technique for mitigating the interference in wireless networks. While previous studies have mainly focused on theoretical gains and algorithms, this paper goes a step further, by assessing IA incorporated to a Coordinated Multi-Point (CoMP)-like network. IA algorithms have been well studied in terms of transmissions performance and signaling cost, albeit for fixed number of users. In the current paper we evaluate the IA technique in more realistic scenarios, in which a scheduling policy is required towards providing service for a whole population of users while the sheer number of involved channels change all the time. The IA performance is shown to be in between the joint processing and conventional transmission schemes, which are distinguished by the coordination (or the lack of it) among the transmitters. By analyzing the impact of different scheduling policies based on distances between subspaces, it is concluded that the channel gains should not be disregarded by the schedulers when trying to improve system capacity.

Analysis of interference alignment for wireless communication with external interference

In order to better cope with the increasing levels of interference in wireless cellular systems, interference mitigation techniques that consider a certain degree of coordination/cooperation among cells have been recently employed, such as Joint Processing (JP) and Interference Alignment (IA). In this paper we evaluate the performance of different IA-based algorithms in the presence of uncoordinated external interference, with JP schemes used as a benchmark. Sum rate and Bit Error Rate (BER) results are presented for different external interference scenarios and it is shown that there is trade-off between IA and JP, and that for high external interference levels IA algorithms modified to handle this external interference can achieve better BER performances.

Interference Alignment, Concepts and Algorithms for Wireless Systems

This chapter describes several aspects of the Interference Alignment (IA) technique with a focus on the spatial domain. The basic idea of Interference Alignment consists in precoding the transmitted signals such that they are aligned at the receiver where they constitute interference, while at the same time disjointed from the desired signal. This alignment limits the generated interference to a subspace at each receiver, which in turn leaves the remaining dimensions free from any interference. Most of the literature on IA considers an idealized scenario with perfect CSI available at the transmitter. In this chapter some well known IA algorithms from the literature are described, also with simulation results for this idealized scenario. Afterwards, some insights are provided on the impact of imperfections, where CSI error and transmit antenna correlation are included within the channel model. Finally, a systemic context is considered where IA is analyzed from a system-level point-of-view, for which some insights on complexity issues are also provided

Block diagonalization with subspace based external interference mitigation

In this work we propose a variation to the Block Diagonalization (BD) algorithm described that mitigates the interference from an external interference source which does not participate in the joint transmission inherent to the BD algorithm. The idea consists of precoding the signal at the transmission side so that the received signal at each receiver lies in a subspace orthogonal to the subspace containing the external interference. It is similar to how interference alignment algorithms work, but here instead of limiting the caused interference at the unintended receivers to a specific subspace, we are limiting the desired signal at the intended receivers. Since this “limiting” aspect reduces the dimensions available for the useful signal, a trade-off is involved between how many useful streams can be transmitted and how much of the external interference energy can be canceled. The proposed algorithm is analyzed and we show different metrics that can be used to determine the “good point” in this trade-off.