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In this work, we propose a novel low-complexity reduced-rank scheme andconsider its application to linear interference suppression in direct-sequenceultra-wideband (DS-UWB) systems. Firstly, we investigate a generic reduced-rankscheme that jointly optimizes a projection vector and a reduced-rank filter byusing the minimum mean-squared error (MMSE) criterion. Then a low-complexityscheme, denoted switched approximation of adaptive basis functions (SAABF), isproposed. The SAABF scheme is an extension of the generic scheme, in which thecomplexity reduction is achieved by using a multi-branch framework to simplifythe structure of the projection vector. Adaptive implementations for the SAABFscheme are developed by using least-mean squares (LMS) and recursiveleast-squares (RLS) algorithms. We also develop algorithms for selecting thebranch number and the model order of the SAABF scheme. Simulations show that inthe scenarios with severe inter-symbol interference (ISI) and multiple accessinterference (MAI), the proposed SAABF scheme has fast convergence andremarkable interference suppression performance with low complexity.

Linear Reduced-Rank Interference Suppression for DS-UWB Systems Using Switched Approximations of Adaptive Basis Functions