Adaptive filter theory (3rd ed.)
Adaptive filter theory (3rd ed.)
Algorithms for Statistical Signal Processing
Algorithms for Statistical Signal Processing
Wireless Communications Systems: Advanced Techniques for Signal Reception
Wireless Communications Systems: Advanced Techniques for Signal Reception
Reduced-rank adaptive filtering using Krylov subspace
EURASIP Journal on Applied Signal Processing
EURASIP Journal on Applied Signal Processing
Introduction to ultra wideband communication systems, an
Introduction to ultra wideband communication systems, an
Reduced-rank adaptive filtering
IEEE Transactions on Signal Processing
Study of the transient phase of the forgetting factor RLS
IEEE Transactions on Signal Processing
Channel models for ultrawideband personal area networks
IEEE Wireless Communications
IEEE Transactions on Wireless Communications - Part 2
A multistage representation of the Wiener filter based on orthogonal projections
IEEE Transactions on Information Theory
Multiuser detection for DS-CDMA UWB in the home environment
IEEE Journal on Selected Areas in Communications
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In this paper a range of reduced-rank adaptive multiuser detectors (MUDs) are proposed and investigated for the hybrid direct-sequence time-hopping ultrawide bandwidth (DS-TH UWB) systems. The adaptive MUDs are operated based on the recursive least square (RLS) principles. Three types of reduced-rank techniques are investigated, which are the principal component (PC), cross-spectral metric (CSM) and Taylor polynomial approximation (TPA). These reduced-rank adaptive techniques are beneficial to achieving low-complexity, high spectral-efficiency and robust detection in hybrid DSTH UWB systems. In this contribution bit error rate (BER) performance of the hybrid DS-TH UWB systems using proposed reduced-rank adaptive MUDs is investigated by simulations, when communicating over UWB channels modelled by the Saleh-Valenzuela (S-V) channel model. Our simulation results show that, given a sufficiently high rank of the detection subspace, the reduced-rank adaptive MUDs are capable of achieving a similar BER performance as that of the full-rank ideal minimum mean-square error MUD (MMSE-MUD) but with significantly lower detection complexity. Furthermore, the TPA-based reduced-rank adaptive MUD is capable of yielding a better BER performance than the PC- or CSM-based reduced-rank adaptive MUD, when the same but relatively low rank detection subspace is assumed.