Maximum-Likelihood Sequence Detection of Multiple Antenna Systems over Dispersive Channels via Sphere Decoding

Multiple antenna systems are capable of providing high data rate transmissions over wireless channels. When the channels are dispersive, the signal at each receive antenna is a combination of both the current and past symbols sent from all transmit antennas corrupted by noise. The optimal receiver is a maximum-likelihood sequence detector and is often considered to be practically infeasible due to high computational complexity (exponential in number of antennas and channel memory). Therefore, in practice, one often settles for a less complex suboptimal receiver structure, typically with an equalizer meant to suppress both the intersymbol and interuser interference, followed by the decoder. We propose a sphere decoding for the sequence detection in multiple antenna communication systems over dispersive channels. The sphere decoding provides the maximum-likelihood estimate with computational complexity comparable to the standard space-time decision-feedback equalizing (DFE) algorithms. The performance and complexity of the sphere decoding are compared with the DFE algorithm by means of simulations

CIO Performance Measurement

Over the last decades, the academy and the community of practice have described the differences in CIO profiles recognizing that the challenges posed by the technological development and the evolution of business models require a wide array of abilities and skills that not always match companies and individuals. If the classic idea of ‘what you measure is what you get’ is also true in IT, then a possible explanation of the misalignments of IS/IT units may lie in the wrong measurement of the expected performances and results of CIOs. This conceptual article explores and describes the effects of performance management and analyzes how it could affect the performance of the CIO

PasMoQAP: A Parallel Asynchronous Memetic Algorithm for solving the Multi-Objective Quadratic Assignment Problem

Multi-Objective Optimization Problems (MOPs) have attracted growing attention during the last decades. Multi-Objective Evolutionary Algorithms (MOEAs) have been extensively used to address MOPs because are able to approximate a set of non-dominated high-quality solutions. The Multi-Objective Quadratic Assignment Problem (mQAP) is a MOP. The mQAP is a generalization of the classical QAP which has been extensively studied, and used in several real-life applications. The mQAP is defined as having as input several flows between the facilities which generate multiple cost functions that must be optimized simultaneously. In this study, we propose PasMoQAP, a parallel asynchronous memetic algorithm to solve the Multi-Objective Quadratic Assignment Problem. PasMoQAP is based on an island model that structures the population by creating sub-populations. The memetic algorithm on each island individually evolve a reduced population of solutions, and they asynchronously cooperate by sending selected solutions to the neighboring islands. The experimental results show that our approach significatively outperforms all the island-based variants of the multi-objective evolutionary algorithm NSGA-II. We show that PasMoQAP is a suitable alternative to solve the Multi-Objective Quadratic Assignment Problem.Comment: 8 pages, 3 figures, 2 tables. Accepted at Conference on Evolutionary Computation 2017 (CEC 2017

A Historical Account of Types of Fuzzy Sets and Their Relationships

In this paper, we review the definition and basic properties of the different types of fuzzy sets that have appeared up to now in the literature. We also analyze the relationships between them and enumerate some of the applications in which they have been used

Energy-Efficient Cooperative Spectrum Sensing based on Stochastic Programming in Dynamic Cognitive Radio Sensor Networks Normal

Nowadays, Cognitive Radio Sensor Networks (CRSN) arise as an emergent technology to deal with the spectrum scarcity issue and the focus is on devising novel energy-efficient solutions. In static CRSN, where nodes have spatial fixed positions, several reported solutions are implemented via sensor selection strategies to reduce consumed energy during cooperative spectrum sensing. However, energy-efficient solutions for dynamic CRSN, where nodes are able to change their spatial positions due to their movement, are nearly reported despite today's growing applications of mobile networks. This paper investigates a novel framework to optimally predict energy consumption in cooperative spectrum sensing tasks, considering node mobility patterns suitable to model dynamic CRSN. A solution based on the Kataoka criterion is presented, that allows to minimize the consumed energy. It accurately estimates -with a given probability-the spent energy on the network, then to derive an optimal energy-efficient solution. An algorithm of reduced-complexity is also implemented to determine the total number of active nodes improving the exhaustive search method. Proper performance of the proposed strategy is illustrated by extensive simulation results for pico-cells and femto-cells in dynamic scenarios.This work was supported in part by the DICYT Project, Direction of Research, Development and Innovation, Universidad de Santiago de Chile, USACH, under Grant 061813KC, in part by the CONICYT-PFCHA/Doctorado Nacional/2016-21160292, and in part by the Spanish National Project TERESA-ADA (MINECO/AEI/FEDER, UE) under Grant TEC2017-90093-C3-2-R

Project-Team RMoD 2013 Activity Report

Activity Report 2013 Project-Team RMOD Analyses and Languages Constructs for Object-Oriented Application Evolutio

ICT-related transformations in Latin American metropolises

The use and application of ICT within and between cities is resulting in significant urban transformations, making cities more connected as well as more complex. A sub-discipline of urban studies - urban ICT studies - has recently emerged to explore, analyse and theorise how the technological advances are transforming urban forms, urban processes and the perceptions of urban life. ICT-related transformations in cities of the developing world, however, have not received enough academic attention until now. This book makes a contribution to the field of urban ICT studies in cities of the South, by exploring the ICT-related transformations in the Latin American urban scene. Based on Gabriel Dupuy’s notion of ‘urbanism of networks’, this explorative research identifies and analyses the recent transformations at three levels: the ICT infrastructure networks, the networks of production and consumption of ICTs in the local urban economy, and the diffusion of digital connectivity in everyday life. The book also presents the situation of digital connectivity in Buenos Aires and Lima, selected as case-studies because singular ICT-related processes are occurring in these two large metropolises. Besides from identifying the urban main trends at the different levels, the results have been also useful to spell out the main trends regarding urban functioning and the urban form, as well as the new problems and new opportunities that the introduction and development of ICTs bring to Latin American cities. The main findings point out that Latin American metropolises have great assets at the infrastructural level as main nodes of the ICT backbones infrastructures. However, there is a profound contradiction between the ICT-related developments occurring in the urban economies, and the social and cultural life of the cities. The low performance of the Latin American metropolises regarding their integration in the global economy and the production of science and technology are in stark contrast with the eagerness of Latin Americans to be connected and to be able to participate as citizens in the network society. These contradiction constitute the largest problem of the future of the metropolises