On Detection Issues in the SC-based Uplink of a MU-MIMO System with a Large Number of BS Antennas

This paper deals with SC/FDE within a MU-MIMO system where a large number of BS antennas is adopted. In this context, either linear or reduced-complexity iterative DF detection techniques are considered. Regarding performance evaluation by simulation, appropriate semi-analytical methods are proposed. This paper includes a detailed evaluation of BER performances for uncoded 4-Quadrature Amplitude Modulation (4-QAM) schemes and a MU-MIMO channel with uncorrelated Rayleigh fading. The accuracy of performance results obtained through the semi-analytical simulation methods is assessed by means of parallel conventional Monte Carlo simulations, under the assumptions of perfect power control and perfect channel estimation. The performance results are discussed in detail, with the help of selected performance bounds. We emphasize that a moderately large number of BS antennas is enough to closely approximate the SIMO MFB performance, especially when using the suggested low-complexity iterative DF technique, which does not require matrix inversion operations. We also emphasize the achievable "massive MIMO" effects, even for strongly reduced-complexity linear detection techniques, provided that the number of BS antennas is much higher than the number of antennas which are jointly employed in the terminals of the multiple autonomous users.Comment: 7 pages, 4 figure

The Effects of Additive Outliers and Measurement Errors when Testing for Structural Breaks in Variance

This paper discusses the asymptotic and finite-sample properties of CUSUM-based tests for detecting structural breaks in volatility in the presence of stochastic contamination, such as additive outliers or measurement errors. This analysis is particularly relevant for financial data, on which these tests are commonly used to detect variance breaks. In particular, we focus on the tests by Inclán and Tiao [IT] (1994) and Kokoszka and Leipus [KL] (1998, 2000), which have been intensively used in the applied literature. Our results are extensible to related procedures. We show that the asymptotic distribution of the IT test can largely be affected by sample contamination, whereas the distribution of the KL test remains invariant. Furthermore, the break-point estimator of the KL test renders consistent estimates. In spite of the good large-sample properties of this test, large additive outliers tend to generate power distortions or wrong break-date estimates in small samples.

ON THE SMALL SAMPLE PROPERTIES OF DICKEY FULLER AND MAXIMUM LIKELIHOOD UNIT ROOT TESTS ON DISCRETE-SAMPLED SHORT-TERM INTEREST RATES

Testing for unit roots in short-term interest rates plays a key role in the empirical modelling of these series. It is widely assumed that the volatility of interest rates follows some time-varying function which is dependent of the level of the series. This may cause distortions in the performance of conventional tests for unit root nonstationarity since these are typically derived under the assumption of homoskedasticity. Given the relative unfamiliarity on the issue, we conducted an extensive Monte Carlo investigation in order to assess the performance of the DF unit root tests, and examined the effects on the limiting distributions of test procedures (t- and likelihood ratio tests) based on maximum likelihood estimation of models for short-term rates with a linear drift.Unit root, interest rates, CKLS model.

On the Small Sample Properties of Dickey Fuller and Maximum Likelihood Unit Root Tests on Discrete-Sampled Short-Term Interest Rates

Testing for unit roots in short-term interest rates plays a key role in the empirical modelling of these series. It is widely assumed that the volatility of interest rates follows some time-varying function which is dependent of the level of the series. This may cause distortions in the performance of conventional tests for unit root nonstationarity since these are typically derived under the assumption of homoskedasticity. Given the relative unfamiliarity on the issue, we conducted an extensive Monte Carlo investigation in order to assess the performance of the DF unit root tests, and examined the effects on the limiting distributions of test procedures (t- and likelihood ratio tests) based on maximum likelihood estimation of models for short-term rates with a linear drift.Unit root, interest rates, CKLS model.

A Multi-Criteria Approach for Irrigation Water Management

The major implications that the European Union (EU) Water Framework Directive (WFD) may have in irrigated agriculture were analysed using alternative water policy measures. The consequences of policy change were evaluated in a case study (Baixo Alentejo, Portugal), using a Multi-Criteria Decision Making (MCDM) model that simulates farmers’ preferred behaviour. The study compares the effects of water pricing (volumetric and flat tariffs) and consumption quotas, in farmer’s income, water agency revenues, agricultural employment and water demand for irrigation. Model results indicate that the adjustments in farmer’s responses are dependent on the policy strategy enforced and on the policy level.Water Framework Directive, Flat Pricing, Volumetric Pricing, Multi- Objective Programming, Water Management, Portugal,

Spatial Interdependence of Brazilian Exports: Impacts on Regional Labor Markets

This paper analyzes the interdependence among Brazilian states associated with employment generation by the export sector. Using a unique database — an interstate input-output table for 1996 — employment multipliers are calculated for six different skill groups. Multiplier decomposition techniques are also used in order to reveal intrastate and interstate patterns of dependence. The analysis of the regional impacts of state exports on employment suggests a concentration of skilled labor content in the states in the Southeastern and Southern regions. More developed states benefit to a great extent from Brazilian exports, responding directly and indirectly to the demand for skilled workers.