Least Mean Square Aided Adaptive Detection in Hybrid Direct-Sequence Time-Hopping Ultrawide Bandwidth Systems

In this contribution an adaptive detection scheme based on least mean square (LMS) principles is proposed and investigated in the context of the hybrid direct-sequence time-hopping ultrawide bandwidth (DS-TH UWB) systems. 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. Furthermore, 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 the sake of comparison with that of the hybrid DS-TH UWB. Our study and simulation results show that the LMS-aided adaptive detection can be a feasible detection scheme for deployment in practical DS-, TH- or hybrid DS-TH UWB systems. It can be shown that, with the aid of a training sequence of reasonable length, the considered UWB schemes are capable of achieving a BER performance which is close to that achieved by the minimum mean-square error (MMSE) detector with perfect channel knowledge.

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