  Cluster-sparse channels often exist in frequencyselective fading broadband
communication systems. The main reason is received scattered waveform exhibits
cluster structure which is caused by a few reflectors near the receiver.
Conventional sparse channel estimation methods have been proposed for general
sparse channel model which without considering the potential cluster-sparse
structure information. In this paper, we investigate the cluster-sparse channel
estimation (CS-CE) problems in the state of the art orthogonal
frequencydivision multiplexing (OFDM) systems. Novel Bayesian clustersparse
channel estimation (BCS-CE) methods are proposed to exploit the cluster-sparse
structure by using block sparse Bayesian learning (BSBL) algorithm. The
proposed methods take advantage of the cluster correlation in training matrix
so that they can improve estimation performance. In addition, different from
our previous method using uniform block partition information, the proposed
methods can work well when the prior block partition information of channels is
unknown. Computer simulations show that the proposed method has a superior
performance when compared with the previous methods.
