Efficient channel estimation in OWC systems using adaptive algorithms

Maintaining the efficiency of optical wireless communication (OWC) systems with channel equalization is a crucial problem. In this paper, different adaptive channel estimation algorithms are studied to allow optical wireless channel equalization. The adaptive channel estimation algorithms considered are standard least mean square (LMS) and LMS with activity detection guidance (ADG) and tap decoupling (TD). Random inputs are used in the channel estimation process. These inputs are of white and color natures. Simulation results prove that the LMS algorithm with ADG is fair enough for the channel estimation problem for white inputs. On the other hand, for colored inputs, the TD is required for correct estimation of channel taps. The asymptotic error performance of the channel estimators is directly proportional to the product of step size, number of estimated taps and noise variance. So, evaluation and comparison of the proposed algorithm with the LMS algorithm are introduced with unit noise variance, 0.07 and 0.01 noise variances with a fixed correlation factor. Thus, we could improve and get the best asymptotic performance and convergence rate of the proposed channel estimator.