Linear Interference Suppression in the Frequency Domain for DS-UWB Systems Using Biased RLS Estimation with Adaptive Shrinkage Factors

Abstract:
In this work, biased algorithms with adaptive shrinkage factors are introduced to the interference suppression scenario. The proposed algorithms with linear receivers improve the performance of the conventional least squares (LS) solution in terms of mean-squared error (MSE), while requiring a very modest increase in complexity. An extension of the Cramér-Rao Lower Bound (CRLB) is computed in order to serve as a performance benchmark for the MSE performance of the biased algorithms. Simulations are carried out for a single-carrier frequency domain equalization (SC-FDE) of direct-sequence ultra-wideband (DS-UWB) systems, where the LS solution is recursively computed by using the recursive least-square (RLS) algorithm. The biased technique is then employed to improve the RLS estimator in terms of MSE. It is shown that the biased algorithms can accelerate the convergence rate and bring overall performance gain in the scenarios of low signal-to-noise ratio (SNR) and short data support.