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2011•Unpublished venueRequires access

MAP estimation of CFO and STO for a convolutionally coded OFDM system

Anushree Neogi, Abhijit Mitra

Open publisher page 1 citations

Abstract

We propose a maximum a-posteriori (MAP) based blind algorithm for carrier frequency offset (CFO) and symbol timing offset (STO) estimation, for a convolutionally coded orthogonal frequency division multiplexing (COFDM) system, in an additive white Gaussian noise (AWGN) channel. We derive the MAP estimators mathematically. It is observed that though the MAP metric for CFO estimation gives a good performance for an AWGN channel, the MAP metric for STO estimation is unable to provide satisfactory performance.

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What this paper is about

We propose a maximum a-posteriori (MAP) based blind algorithm for carrier frequency offset (CFO) and symbol timing offset (STO) estimation, for a convolutionally coded orthogonal frequency division multiplexing (COFDM) system, in an additive white Gaussian noise (AWGN) channel. We derive the MAP estimators mathematically. It is observed that though the MAP metric for CFO estimation gives a good performance for an AWGN channel, the MAP metric for STO estimation is unable to provide satisfactory performance.

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Available abstract

We propose a maximum a-posteriori (MAP) based blind algorithm for carrier frequency offset (CFO) and symbol timing offset (STO) estimation, for a convolutionally coded orthogonal frequency division multiplexing (COFDM) system, in an additive white Gaussian noise (AWGN) channel. We derive the MAP estimators mathematically. It is observed that though the MAP metric for CFO estimation gives a good performance for an AWGN channel, the MAP metric for STO estimation is unable to provide satisfactory performance.

Key concepts: Carrier frequency offset, Additive white Gaussian noise, Orthogonal frequency-division multiplexing, Maximum a posteriori estimation, Estimator, Computer science, Algorithm, Bit error rate

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