Adaptive filter theory (3rd ed.)
Adaptive filter theory (3rd ed.)
Indefinite-quadratic estimation and control: a unified approach to H2 and H∞ theories
Indefinite-quadratic estimation and control: a unified approach to H2 and H∞ theories
Sigma-point kalman filters for probabilistic inference in dynamic state-space models
Sigma-point kalman filters for probabilistic inference in dynamic state-space models
Performance analysis of LTE downlink system using relay-based selective transmission
Personal and Ubiquitous Computing
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In an uplink transmission of a coded orthogonal frequency division multiple access (C-OFDMA) system, channel estimation, time and frequency synchronization has to be addressed. For this purpose a control data, i.e. a known training sequence called "preamble" and pilot sub-carriers are used. As an alternative to the classic scheme and in order to maximize the data rate, we propose a non-pilot aided estimator based on an iterative architecture that does not require pilot sub-carriers. Our approach combines 1/ the so-called minimum mean square error successive detector to estimate the signal sent by each user 2/ a recursive method estimating the CFOs. Various algorithms such as the extended Kalman filter, the sigma-point Kalman filters and the extended H 驴 filter are tested and their performances are compared in terms of convergence speed and estimation accuracy. When considering an interleaved OFDMA uplink system over a Rayleigh fading channel, simulation results clearly show the efficiency of the proposed algorithm in terms of CFO estimation and bit error rate performances.