Paper

This study proposes two low-complexity iterative successive interference cancellation schemes for OFDM systems with doubly selective channels, leveraging Krylov subspace optimization methods to efficiently mitigate inter-carrier interference.

A novel stochastic gradient pursuit algorithm adaptively equalizes sparse multipath channels by exploiting their inherent sparsity and outperforms existing methods in terms of convergence speed.

A novel application of compressed sensing techniques significantly improves decision feedback equalization of sparse wireless channels by exploiting filter sparsity.

This research proposes two novel adaptive decision feedback equalization schemes that exploit sparsity in both channel impulse responses and equalizer filters, leading to improved performance and computational efficiency.