Greedy Deterministic Pilot Pattern Algorithms for OFDM Sparse Channel Estimation

In this paper, deterministic pilot pattern design for sparse channel estimation in orthogonal frequency division multiplexing (OFDM) systems is investigated. Pilot subcarriers are essential for channel estimation and especially the selection of pilot subcarriers significantly affect compressive sensing based channel estimation performance. With straightforward searching and based on minimizing the coherence of the measurement matrix, three greedy deterministic pilot pattern optimization algorithms for sparse channel estimation in OFDM systems is proposed. In addition, a minimum distance term is introduced, which distance of pilots to each other must be integer multiples of this minimum distance term. By using the proposed minimum distance term, the algorithm only searches possible subcarriers, which lead to fast runtime and low complexity. Orthogonal matching pursuit is used as the recovery method for estimation of the channel taps. Simulation results demonstrate that the proposed algorithms are more efficient than the exhaustive search for pilot pattern design.

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