## 1 Introduction  
Filter bank multicarrier(FBMC) techniques have drawn increasing attention from many researchers [1; 2; 3]. In recent years,it has become a competitive alternative to the most famous and accepted Orthogonal Frequency Division Multiplexing (OFDM) schemes, particularly in wireless communication systems. As a potential candidate multicarrier modulation scheme for next generation wireless communication networks [4; 5; 6; 7; 8], filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) is a particular type of FBMC. It utilizes time frequency localization (TFL) well and it employs a property pulse shaping based filter [9] bank, which has a theoretically higher spectral efficiency [10; 11]. FBMC/OQAM also demonstrates robustness to frequency offset and Doppler spread. Besides, CP is not needed in FBMC/OQAM systems, which can provide higher data rates than conventional OFDM [12]. FBMC/OQAM system has its root in the pioneering works of [PERSON] [13] and [PERSON] [14] who introduced multicarrier techniques over two decades ago. However, with the conventional OFDM transmission complex-valued symbols in a given symbol rate, FBMC/OQAM transmits real-valued symbols at the symbol rate of two times. The subcarrierfunctions are only orthogonal in the real field, therefore, an inherent imaginary interference among neighboring subcarriers and symbols is always existed. The intrinsic inter-carrier/inter-symbol interference will complicate channel estimation processing. Hence, the existing OFDM channel estimation methods cannot be directly applied in FBMC/OQAM systems. Many training schemes and related estimation methods have been recently researched in literature [15; 16; 17; 18]. The two classical preamble-based methods are interference approximation method (IAM) [15; 16] and interference cancellation method (ICM) [17; 18]. They can be summed up as aiming at avoiding the intrinsic interference or constructively utilizing it to improve the estimation performance. However, it has been proved that the performance of estimator utilizing preamble-based method is inefficient since it is difficult to fully avoid intrinsic interference. A number of efforts have been devoted to improving the performance of channel estimation. A coded auxiliary pilot channel estimation method for FBMC/OQAM has been proposed [19]. The method is using coded auxiliary pilot symbols to eliminate the imaginary interference on each scatted pilot. Semi-blind and blind symbol timing estimation methods for FBMC/OQAM system have also been studied [20; 21]. However, these schemes have a higher computational complexity, and the phase ambiguity may occur and need longer observation data, which, to some extent, limits the availability. A more attractive approach to obtain well channel estimation performance is the recently researched compressive sensing (CS) method [22; 23; 24; 25; 26; 27], where the wireless channels in practice tend to exhibit a sparse multipath structure. Some channel estimation based on CS methods for OFDM systems have been studied in the past few years [28; 29; 30; 31]. However, there are only few literatures about CS-based channel estimation for FBMC/OQAM systems. An improved IAM that reconstructs channel impulse response by utilizing the orthogonal matching pursuit (OMP) algorithm based on channel estimation for FBMC/OQAM has been proposed in [32]. It is proved that the OMP [33] based method can get remarkable performance improvement compared with the conventional preamble based method. For the most greedy CS algorithms, such as OMP and compressive sampling matching pursuit (CoSaMP) [34], the sparsitylevel of the channel is given as a priori information. However, the sparsity of the channel is usually unknown in most practical application scenarios. In this paper, a novel channel estimation method named sparse adaptive regularized compressive sampling matching pursuit (ARCoSaMP) is proposed for FBMC/QOAM transmission networks.