Normalised Least Mean-Square Aided Decision-Directed Adaptive Detection in Hybrid Direct-Sequence Time-Hopping UWB Systems

In this contribution decision-directed adaptive detection scheme based on normalised least mean-square (DD/NLMS) principles is proposed and investigated for the hybrid direct- sequence time-hopping ultrawide bandwidth (DS-TH UWB) system. The bit-error-rate (BER) performance of the hybrid DS-TH UWB system is investigated when communicating over the UWB channels modelled by the Saleh-Valenzuela (S-V) channel model. Since both the pure DS-UWB and pure TH-UWB constitute special examples of the hybrid DS-TH UWB, their BER performance is also investigated in this contribution for sake of comparison with that of the hybrid DS-TH UWB. Our study and simulation results show that the DD/NLMS-aided adaptive detection constitutes a feasible detection scheme for practical DS-, TH- or hybrid DS-TH UWB systems. With the aid of a training sequence of reasonable length, our study shows that the considered UWB schemes are capable of achieving the BER performance that is close to that achieved by the minimum mean-square error (MMSE) detector with perfect channel knowledge. Furthermore, the DD adaptive techniques may be employed by UWB systems in order to improve their spectral-efficiency.