Abstract
In this paper a new computationally efficient and high performance channel estimation algorithm is proposed for the indoor visible light communication (VLC) sparse channels in the presence of a clipping noise. The clipping noise is modelled as a Gaussian mixture and, a first time in the literature, the matching pursuit (MP) and the space-alternating expectation- maximization (SAGE) algorithms are combined into the new estimation, called the SAGE-MP algorithm for iteratively estimating the sparse channel coefficients as well as their positions efficiently. The MP algorithm is also employed to determine the initial values of the joint iterative algorithm. Computed simulations indicates that the SAGE-MP algorithm converge in 3 iterations at most and yields excellent bit error rate (BER) and mean-square error (MSE) performances for DC-biased optical OFDM (DCO-OFDM) based systems.
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