Channel estimation for OFDM system in atmospheric optical communication based on compressive sensing

Abstract

Orthogonal frequency division multiplexing (OFDM) technique applied to the atmospheric optical communication can improve data transmission rate, restrain pulse interference, and reduce effect of multipath caused by atmospheric scattering. Channel estimation, as one of the important modules in OFDM, has been investigated thoroughly and widely with great progress. In atmospheric optical communication system, channel estimation methods based on pilot are common approaches, such as traditional least-squares (LS) algorithm and minimum mean square error (MMSE) algorithm. However, sensitivity of the noise effects and high complexity of computation are shortcomings of LS algorithm and MMSE algorithm, respectively. Here, a new method based on compressive sensing is proposed to estimate the channel state information of atmospheric optical communication OFDM system, especially when the condition is closely associated with turbulence. Firstly, time-varying channel model is established under the condition of turbulence. Then, in consideration of multipath effect, sparse channel model is available for compressive sensing. And, the pilot signal is reconstructed with orthogonal matching tracking (OMP) algorithm, which is used for reconstruction. By contrast, the work of channel estimation is completed by LS algorithm as well. After that, simulations are conducted respectively in two different indexes -signal error rate (SER) and mean square error (MSE). Finally, result shows that compared with LS algorithm, the application of compressive sensing can improve the performance of SER and MSE. Theoretical analysis and simulation results show that the proposed method is reasonable and efficient.