In the time-domain, symbol by symbol transmission multiuser DS-UWB systems are considered. We first investigate a generic reduced-rank scheme based on the concept of joint and iterative optimization (JIO) that jointly optimizes a projection vector and a reduced-rank filter by using the minimum mean-squared error (MMSE) criterion. A low-complexity scheme, named Switched Approximations of Adaptive Basis Functions (SAABF), is proposed as a modification of the generic scheme, in which the complexity
reduction is achieved by using a multi-branch framework to simplify the structure of the projection vector. Adaptive implementations for the SAABF scheme are developed by
using least-mean squares (LMS) and recursive least-squares (RLS) algorithms. We also develop algorithms for selecting the branch number and the model order of the SAABF
scheme. Secondly, a novel linear reduced-rank blind adaptive receiver based on JIO and the constrained constant modulus (CCM) design criterion is proposed that offers higher spectrum efficiency. Adaptive implementations for the blind JIO receiver are developed by using the normalized stochastic gradient (NSG) and RLS algorithms. In order to obtain a low-complexity scheme, the columns of the projection matrix with the RLS algorithm are updated individually. Blind channel estimation algorithms for both versions (NSG and RLS) are implemented. Assuming the perfect timing, the JIO receiver only requires the knowledge of the spreading code of the desired user and the received data.
In the frequency-domain, we propose two adaptive detection schemes based on singlecarrier frequency domain equalization (SC-FDE) for the block by block transmission multiuser DS-UWB systems, which are termed structured channel estimation (SCE) and direct adaptation (DA). Both schemes use the MMSE linear detection strategy and employ
a cyclic prefix. In the SCE scheme, we perform the adaptive channel estimation in the frequency-domain and implement the despreading in the time-domain after the FDE. In
this scheme, the MMSE detection requires the knowledge of the number of users and the noise variance. For this purpose, we propose low-complexity algorithms for estimating
these parameters. In the DA scheme, the interference suppression task is fulfilled with only one adaptive filter in the frequency-domain and a new signal expression is adopted to simplify the design of such a filter. LMS, RLS and conjugate gradient (CG) adaptive algorithms are then developed for both schemes. Another strand of investigation considers adaptive detectors and frequency domain
equalization for multiuser DS-UWB systems with block transmissions and biased estimation methods. Biased estimation techniques can provide performance improvements
to the existing unbiased estimation algorithms. In this work, biased adaptive estimation techniques based on shrinkage estimators are devised and incorporated into RLS-type algorithms. For the SCE scheme, automatic shrinkage factor mechanisms are proposed and incorporated into RLS estimators, obtaining a lower MSE of the channel estimation. For the DA scheme, the automatic shrinkage factors are incorporated directly to the adaptive
receiver weights. The results show that a shorter data support is required by the proposed biased DA-RLS technique. An analysis of fundamental estimation limits of the proposed frequency domain biased estimators is included along with the derivation of appropriate Cramer-Rao lower bounds (CRLB).
