Modeling and Estimation of Wireless Multipath Channels: An Application within Pilot-assisted Channel Estimation for Downlink OFDM
Author
Jakobsen, Morten Lomholt
Term
4. term
Education
Publication year
2009
Pages
121
Abstract
Denne afhandling undersøger modellering og estimering af trådløse multipath-kanaler i en pilotassisteret kanalestimeringsramme for nedlink OFDM. Motivation: Metoder, der er robuste over for manglende forhåndsviden om kanalen, kræver typisk et stort overhead af pilotsymboler. Et alternativ er at udnytte en parametrisk kanalmodel, som forudsætter viden om tidsvarierende multipath-forsinkelser. Det centrale spørgsmål er, om et modtagerdesign praktisk kan indeholde et lavkomplekst og tilstrækkeligt præcist modul til estimering af disse forsinkelser. Afhandlingen gennemgår og evaluerer metoder til forsinkelsesestimering med særligt fokus på ESPRIT-algoritmen og analyserer, hvordan den antagne kanalmodel (statisk versus dynamisk) påvirker ydeevnen. Under statiske antagelser opnår ESPRIT tilfredsstillende nøjagtighed og systemydelse, men under mere realistiske, dynamiske forhold med tidsvarierende forsinkelser leverer metoden ikke tilstrækkelig nøjagtighed. På den baggrund undersøges alternative tilgange i en oversigtspræget studie, hvor foreløbige resultater peger på, at den sekventielle beamforming-algoritme kan være lovende med hensyn til ydeevne, robusthed og beregningskompleksitet, om end yderligere undersøgelser er nødvendige. Konklusionen er, at forsinkelsesestimatorer bør målrettes dynamiske kanaler, og at alternativer til ESPRIT bør udvikles og afprøves.
This thesis examines modeling and estimation of wireless multipath channels for pilot-assisted channel estimation in downlink OFDM. The motivation is that methods robust to little or no prior channel knowledge typically require a large overhead of pilot symbols. An alternative is to exploit a parametric channel model that presupposes knowledge of time-varying multipath propagation delays. The core question is whether a receiver can practically include a low-complexity, sufficiently accurate module to estimate these delays. The work reviews and evaluates delay estimation methods with a particular focus on the ESPRIT algorithm and analyzes how performance depends on the assumed channel model (static versus dynamic). Under static assumptions, ESPRIT achieves satisfactory delay accuracy and system performance; under more realistic, dynamic conditions with time-varying delays, it fails to provide adequate accuracy. Motivated by this, the thesis surveys alternative approaches, where preliminary results indicate that the sequential beamforming algorithm may offer a promising trade-off in performance, robustness, and computational complexity, though further investigation is needed. The overall conclusion is that delay estimators should target dynamic channels, and alternatives to ESPRIT merit development and testing.
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