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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Method of Estimating Sparse and Doubly-Dispersive Channels

The large delay and Doppler spreads of skywave high-frequency (HF) channels complicates channel acquisition, especially in low-SNR conditions. Using pilot-symbol assisted modulation, we develop a robust method to acquire channel information by first estimating the power-delay profile (PDP) of the channel, then applying that estimate to obtain the channel coefficients only where the PDP is nonzero. We find the presented approach to be robust at low-SNRs, making it suitable for spread-spectrum and underlay waveforms. We show that this two-stage channel acquisition procedure has three advantages: i),the channel is estimated with fewer terms, reducing complexity; ii), the MSE of the channel estimate is lower than assuming a fixed channel length; and iii), each propagation mode is reliably recovered in high-Doppler conditions. We conclude this paper by presenting results of the developed techniques as applied to a filter-bank multicarrier spread-spectrum (FBMC-SS) waveform.

42 ENGINEERING↗
DOE OSTI2023

Building Alternative Indices of Socioeconomic Status for Population Modeling in Data-Sparse Contexts (Short Paper)

Population modeling requires clear definitions of socioeconomic status (SES) to ensure overall estimate accuracy and locate potentially underserved subpopulations. This presents a challenge as SES can be measured in myriad ways and for divergent purposes, and the data required to calculate these metrics may be lacking, particularly in low and middle income countries (LMICs). To support more refined SES measurement, we explore improvements upon the Demographic and Health Survey’s (DHS) Wealth Index (DHS-WI) using alternative characterizations of SES based on multiple correspondence analysis (MCA) and hierarchical clustering. We produce the MCA-derived metrics first on a full suite of household economic, demographic, and dwelling variables, then on a reduced set of occupant-only SES characteristics. We explore the utility of these metrics relative to DHS-WI based on their ability to 1) differentiate DHS household types and 2) identify mixtures of SES levels within DHS samples and mapped at high spatial resolution. We find that our full suite MCA yields more clearly defined SES segments and that our reduced MCA delineates occupant SES most clearly, suggesting potential pathways to improve upon the DHS-WI in future population modeling efforts for LMICs.

Cunningham, Angela↗