3-D Statistical Channel Model for Millimeter-Wave Outdoor Mobile Broadband Communications

This paper presents an omnidirectional spatial and temporal 3-dimensional statistical channel model for 28 GHz dense urban non-line of sight environments. The channel model is developed from 28 GHz ultrawideband propagation measurements obtained with a 400 megachips per second broadband sliding correlator channel sounder and highly directional, steerable horn antennas in New York City. A 3GPP-like statistical channel model that is easy to implement in software or hardware is developed from measured power delay profiles and a synthesized method for providing absolute propagation delays recovered from 3-D ray-tracing, as well as measured angle of departure and angle of arrival power spectra. The extracted statistics are used to implement a MATLAB-based statistical simulator that generates 3-D millimeter-wave temporal and spatial channel coefficients that reproduce realistic impulse responses of measured urban channels. The methods and model presented here can be used for millimeter-wave system-wide simulations, and air interface design and capacity analyses.Comment: 7 pages, 6 figures, ICC 2015 (London, UK, to appear

Analysis of power line communications for last-hop backhaul in small cells deployment

Publicado en: :(2019-04-05),(José A. Cortes, Francisco J. Cañete, Matías Toril, Luis Díez, Alicia García-Mozos, "Analysis of power line communications for last-hop backhaul in small cells deployment", in Proceedings of the IEEE International Symposium on Power Line Communications and its Applications, 2019.),yEditor(IEEE)The purpose of this work is to study the feasibility of using power line communications (PLC) over outdoor public lighting networks (OPLN) for last-hop backhaul in small cell deployment. The analysis is based on actual noise measurements performed in two OPLN in the city of Málaga (Spain) and on a bottom-up channel simulator, which has been designed according to the physical characteristics and the common practices in such kind of networks. Estimations of the bit-rate achieved by PLC systems following the ITU-T Rec. G.9960 (G.hn) standard, are performed and discussed. Results indicate that PLC is a promising solution for this application.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

A Comparative Study of Machine Learning Models for Tabular Data Through Challenge of Monitoring Parkinson's Disease Progression Using Voice Recordings

People with Parkinson's disease must be regularly monitored by their physician to observe how the disease is progressing and potentially adjust treatment plans to mitigate the symptoms. Monitoring the progression of the disease through a voice recording captured by the patient at their own home can make the process faster and less stressful. Using a dataset of voice recordings of 42 people with early-stage Parkinson's disease over a time span of 6 months, we applied multiple machine learning techniques to find a correlation between the voice recording and the patient's motor UPDRS score. We approached this problem using a multitude of both regression and classification techniques. Much of this paper is dedicated to mapping the voice data to motor UPDRS scores using regression techniques in order to obtain a more precise value for unknown instances. Through this comparative study of variant machine learning methods, we realized some old machine learning methods like trees outperform cutting edge deep learning models on numerous tabular datasets.Comment: Accepted at "HIMS'20 - The 6th Int'l Conf on Health Informatics and Medical Systems"; https://americancse.org/events/csce2020/conferences/hims2