Sparse equalizer design under a quadratic constraint
Sparse equalizers which have fewer nonzero coefficients can significantly reduce the cost of the implementation and computational complexity. The performance of the sparse equalizers heavily depends on the tap selection algorithms. In this paper, a low complexity algorithm based on the forward greedy selection is proposed. The objective of the sparse equalizer design is to reduce the number of nonzero equalizer coefficients under a quadratic constraint with a given tolerance of the performance loss. Furthermore, the performance of the proposed algorithm is analyzed and we obtain the terminal condition for the iteration number of the forward selection algorithm. Simulation results show that the proposed algorithm can reach the same performance or outperform the conventional sparse equalizer schemes, offering a low computational complexity at the same time.