signature waveform 
Robustness of the subspace method for blind signature waveform estimation with respect to channel order in asynchronous DSCDMA


The robustness of the subspace method for blind signature waveform estimation with respect to channel order is analyzed in asynchronous DSCDMA systems theoretically.


Theoretical analysis and simulation results show that the overestimating of the channel order will lead to the degradation of the quality of the estimated signature waveform.


In practice, it is showed that by incorporating the desired user's signature waveform and the auxiliary vector, the information of the user can be identified using the suboptimal subspace method.


The proposed blind adaptive multiuser detector utilizes the signature waveform and time information of the desired user.


This paper also presents an improved robust blind multiuser detection technique based on a subspace approach, which requires only the signature waveform and the timing of the desired user to demodulate that user's signal.


Training Sequence Aided Signature Waveform Estimation


In this paper, we compare the performance of two short training sequence aided signature waveform estimators.


One is maximum likelihood type signature waveform estimator that requires the knowledge of spreading sequences and short training sequences.


Through the simulations, we show the signature waveform estimation performance of both systems and the effect of the estimation error on the performance of a multiuser detector.


A binary data sequence of each user is multiplied by a unique signature waveform to produce a transmitted baseband signal.


Demodulation of DSCDMA signals is conventionally achieved by a bank of filters, each matched to the signature waveform of a user.


In the previous chapters we first developed a wavelet packet based doubly orthogonal signature waveform design for DSCDMA communications.


In this signature waveform design a number of shorter wavelet packets are cascaded to form a longer waveform.


The demodulator on each receive antenna uses a bank of K matched filters, each matched to a different user's signature waveform.


Without loss of generality, suppose that the user one is our desired user whose signature waveform is denoted as s1.

