Research on adaptive equalization algorithm for sparse multipath channel

In order to solve the problem of poor performance of traditional adaptive equalization algorithm in sparse multipath channels, a new adaptive equalization algorithm based on l₂ -norm is proposed. This algorithm takes advantage of the sparsity of equalizer weights in sparse multipath channel, and regards the training process of adaptive equalizer as the weighted sum of sparse signal to dictionary in compressed sensing theory, so as to solve the problems of iterative parameter setting and slow convergence. This new algorithm, which combines l₂ -norm with compressed sensing, not only improves the weight accuracy, but also reduces the computational complexity. Simulation results show that the proposed algorithm can achieve better performance with less computation amount and fewer training sequences, and has a reference value for improving the communication performance of the system.