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Physical Sciences and Mathematics Commons™

Open Access. Powered by Scholars. Published by Universities.®

Electrical and Computer Engineering

Iowa State University

Selected Works

2013

Articles 1 - 2 of 2

Full-Text Articles in Physical Sciences and Mathematics

Joint User Grouping And Linear Virtual Beamforming: Complexity, Algorithms And Approximation Bounds, Mingyi Hong, Zi Xu, Meisam Razaviyayn, Zhi-Quan Luo Oct 2013

Joint User Grouping And Linear Virtual Beamforming: Complexity, Algorithms And Approximation Bounds, Mingyi Hong, Zi Xu, Meisam Razaviyayn, Zhi-Quan Luo

Mingyi Hong

In a wireless system with a large number of distributed nodes, the quality of communication can be greatly improved by pooling the nodes to perform joint transmission/reception. In this paper, we consider the problem of optimally selecting a subset of nodes from potentially a large number of candidates to form a virtual multi-antenna system, while at the same time designing their joint linear transmission strategies. We focus on two specific application scenarios: 1) multiple single antenna transmitters cooperatively transmit to a receiver; 2) a single transmitter transmits to a receiver with the help of a number of cooperative relays. We …

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Derivative Estimation With Local Polynomial Fitting, Kris De Brabanter, Jos De Brabanter, Bart De Moor, Irene Gijbels Jan 2013

Derivative Estimation With Local Polynomial Fitting, Kris De Brabanter, Jos De Brabanter, Bart De Moor, Irene Gijbels

Kris De Brabanter

We present a fully automated framework to estimate derivatives nonparametrically without estimating the regression function. Derivative estimation plays an important role in the exploration of structures in curves (jump detection and discontinuities), comparison of regression curves, analysis of human growth data, etc. Hence, the study of estimating derivatives is equally important as regression estimation itself. Via empirical derivatives we approximate the qth order derivative and create a new data set which can be smoothed by any nonparametric regression estimator. We derive L1 and L2 rates and establish consistency of the estimator. The new data sets created by this technique are …

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