Low-Complexity Reduced-Rank Interference Mitigation Algorithms for DS-UWB Systems

We consider a two-stage framework for linear interference mitigation, in which a transformation performs dimensionality reduction followed by a reduced-rank filter. A generic reduced-rank scheme that jointly optimizes the transformation and the reduced-rank filter by using the minimum mean squared error (MMSE) criterion is investigated. Then, we impose constraints on the design of the transformation and propose the switched approximations of adaptive basis functions (SAABF) scheme, in which the transformation is chosen instantaneously from a set of mapping matrices and adaptive basis functions. Least-mean squares (LMS) algorithms and model-order selection algorithms are also proposed. A complexity analysis shows that the proposed scheme is significantly simpler than the existing reduced-rank schemes. Simulations show remarkable interference mitigation performance in direct-sequence ultra-wideband (DS-UWB) systems.