Speeding up Noise Subspace Estimation Algorithms using an Optimal Diagonal Matrix Step-Size Strategy for MC-CDMA Application

In this paper, we propose a new optimal diagonal-matrix step-size strategy for some noise subspace estimation algorithms. The proposed step-sizes control the decoupled subspace vectors individually as compared to conventional methods where all the subspace vectors are multiplied by the same step-size value. Simulation results show that this optimal diagonal- matrix step-size strategy outperforms the original algorithms as it offers faster convergence rate, smaller steady state error and similar orthogonality error simultaneously. Finally, the algorithms with the proposed step-size strategy are used for blind channel estimation in MC-CDMA system.