Inlämning av Examensarbete / Submission of Thesis

Shravan Kumar Parsi; Sridhar Basa , pp. 47. ING/School of Engineering, 2011.

The work

Författare / Author: Shravan Kumar Parsi, Sridhar Basa,
Titel / Title: SNR Estimation for Preamble-based Wireless OFDM Systems using Extended Kalman Filter
Abstrakt Abstract:

In Orthogonal Frequency Division Multiplexing (OFDM) systems, robustness in frequency selective channels is achieved using adaptable transmission parameters. To reckon these parameters, knowledge of Signal to Noise Ratio (SNR) estimates obtained by channel state information is essential. This necessitates for an appropriate channel estimation scheme to acquire efficient SNR estimates in wireless frequency selective fading channels. Improved Periodic Sequence (IPS) based OFDM system incurs SNR estimates by utilizing Least Squares (LS) channel estimates and adaptively choosing significant Channel Impulse Response (CIR) paths in Discrete Fourier Transform (DFT) interpolation. LS channel estimation scheme is a linear processing method, which disposes for only linear characteristics of wireless channels. In order to contend with the non linearity of frequency selective wireless channels, a non linear Extended Kalman Filter (EKF) estimation scheme is implemented with DFT interpolation in this extended IPS estimation algorithm. The proposed extended IPS estimator outperforms IPS estimator in terms of average SNR and SNR per subcarrier for frequency selective channels.

Ämnesord / Subject: Telekommunikation - Telecommunications

Nyckelord / Keywords: Extended Kalman Filter, Fading channels, Least squares, OFDM, SNR

Publication info

Dokument id / Document id: houn-8mrddu
Program:/ Programme Magisterprogram i Elektroteknik / Master of Science in Electrical Engineering
Registreringsdatum / Date of registration: 10/18/2011
Uppsatstyp / Type of thesis: Masterarbete/Master's Thesis (120 credits)


Handledare / Supervisor: Abbas Mohammed
Examinator / Examiner: Benny Lövström/Abbas Mohammed
Organisation / Organisation: Blekinge Institute of Technology
Institution / School: ING/School of Engineering

+46 455 38 50 00
Anmärkningar / Comments:

Shravan Kumar Parsi - 0091 9949954432
Sridhar Basa - 0091 9676180953

Files & Access

Bifogad uppsats fil(er) / Files attached: bth2011parsi.pdf (970 kB, öppnas i nytt fönster)