WiMAX paves the way for wireless DSL to play a significant role in the broadband wireless access market, especially for rural areas with low population density. Conventional cellular planning methods can be used for point-to-multi-point network design. As an alternative, the Fractional Frequency Reuse (FFR) planning strategy has been recently proposed for cellular systems based on the OFDMA/OFDM radio interface (e.g., WiMAX). In this article we analyze the FFR scheme in rural areas evaluating the increase of the overall system capacity. FFR performances are reported in terms of the average number of bits that can be transmitted per symbol in the area. Finally, comparisons with classical frequency reuse planning are analyzed taking into consideration rural environment characteristics. We show that the FFR scheme can provide extra capacity, slightly penalizing the users at the cell edge. © 2008 IEEE

There are several areas in which organisations can adopt technologies that will support decision-making: artificial intelligence is one of the most innovative technologies that is widely used to assist organisations in business strategies, organisational aspects and people management. In recent years, attention has increasingly been paid to human resources (HR), since worker quality and skills represent a growth factor and a real competitive advantage for companies. After having been introduced to sales and marketing departments, artificial intelligence is also starting to guide employee-related decisions within HR management. The purpose is to support decisions that are based not on subjective aspects but on objective data analysis. The goal of this work is to analyse how objective factors influence employee attrition, in order to identify the main causes that contribute to a worker’s decision to leave a company, and to be able to predict whether a particular employee will leave the company. After the training, the obtained model for the prediction of employees’ attrition is tested on a real dataset provided by IBM analytics, which includes 35 features and about 1500 samples. Results are expressed in terms of classical metrics and the algorithm that produced the best results for the available dataset is the Gaussian Naïve Bayes classifier. It reveals the best recall rate (0.54), since it measures the ability of a classifier to find all the positive instances and achieves an overall false negative rate equal to 4.5% of the total observations.

No abstract

Classical single carrier cell planning is extended to multi-carrier systems operating over frequency selective channels. Extension is achieved by expressing the link outage probability in terms of the statistics of the effective SINR. Two approximations for the link outage probability are obtained by considering Log-Normal and Gaussian assumptions for the derivation of the statistics of the exponential effective SINR. A simplified planning procedure is presented and applied to the calculation of the network parameters for the typical two-cells interference scenario. Results having accuracy within one dB are obtained for a number of sub-carriers greater than six and for an outage target of 5%

No abstract