Blind channel equalization based on iterative weighted Least-Mean squared algorithm
Document Type
Conference Proceeding
Publication Date
12-1-2004
Abstract
Expectation-maximization (EM) criterion has been widely applied for sparse observed data, such as time-varying wireless channel equalization. Previous EM techniques for joint channel estimation and symbol detection had computational complexity exponentially proportional to channel model order. In this paper, we derive an efficient Iterative Weighted Least Mean Squared (IWLMS) algorithm based on EM for blind equalization. Our new IWLMS algorithm, greatly outperforms the popular blind equalization method based on the constant-modulas criteria according to Monte Carlo experiments. © 2004 IEEE.
Publication Source (Journal or Book title)
IEEE Vehicular Technology Conference
First Page
3833
Last Page
3837
Recommended Citation
Xu, D., & Wu, H. (2004). Blind channel equalization based on iterative weighted Least-Mean squared algorithm. IEEE Vehicular Technology Conference, 60 (6), 3833-3837. Retrieved from https://repository.lsu.edu/eecs_pubs/2225