Adaptive Filtering Algorithms In Wireless Communications Applications

The channel constitutes an absolutely necessarily part of communication system, and noise in channel is unavoidable. The question about channel and noise is the basic question in communication system. In this paper, we focus on the application of adaptive filtering algorithms to channel estimation and noise cancelling.Three kinds of simple adaptive filtering algorithms for channel estimation are introduced. One of the algorithms is the Toeplitz preconditioned block conjugate gradient shifting (TBCGS) algorithm. The algorithm is formulated by combining TBCG algorithm with a shifting scheme, as in the optimum block adaptive shifting (OBAS) algorithm. The proposed algorithm is superior to the TBCG algorithm in both convergence rate and adaptation accuracy. The other two algorithms are modified leaky DFT-LMS algorithm and modified shifting LMS algorithm. These two algorithms are nearly blind since they do not require any training sequence or channel statistics, and they can be implemented using only noise variance knowledge. The important is that they provide faster convergence than modified leaky LMS algorithm.In addition, we use the modified leaky LMS algorithm for noise cancelling in this paper. The algorithm does not require another noise signal correlated with the contamination noise, and it can be implemented using only contamination noise variance knowledge. This way overcomes the disadvantage of the traditional adaptive method.