The technique of direct-sequence (DS) code division multiple access (CDMA) cellular systems has been the focus of increased attention. In this thesis, the problem of narrow-band interference (NBI) cancellation for the DS-CDMA communication systems is considered. It has been shown that the performance of single NBI cancellation for CDMA systems by using the non-linear filtering approach, the so-called DDK filter or the MDK filter, is superior to the one using the linear filtering approach. The main concern of this thesis is to deal with the multiple NBI cancellation. This may occur in some practical application, for instance, in the 2.4GHz CDMA system, the bluetooth and wireless LAN may exist in the same frequency band with different power ratio. In this thesis, the nonlinear filtering with fast convergence least square (LS) algorithms, viz., the modified inverse QRD-RLS (IQRD-RLS) and the interior point (IP) LS algorithms, are devised for multiple NBI cancellation in the multi-user CDMA system. In fact, the IQRD-RLS and the IP LS algorithms are known to have better numerical stability and convergence property in the RLS family. Since in the non-linear MDK filter with the IQRD-RLS algorithm, the prediction error £`k,k-1 used in the conventional IQRD-RLS is replaced by the nonlinear function of £l(£`k,k-1), and is defined to as the modified IQRD-RLS algorithm. The merits of the proposed algorithms are verified via computer simulation. We showed that the performance of our proposed algorithms outperformed the one using the conventional nonlinear filtering approach with LMS algorithm, in terms of convergence property and the signal-to-noise ratio improvement (SNRI).

In this thesis, the problem of multiple access interference (MAI) suppression for the multi-carrier (MC) code division multiple access (CDMA) system, based on the wavelet-based (WB) multi-carrier modulation, associated with the combining process is investigated for Rayleigh fading channel. The main concern of this thesis is to derive a new scheme, based on the linearly constrained constant modulus (LCCM) criterion with the robust inverse QR decomposition (IQRD) recursive least squares (RLS) algorithm to improve the performance of the conventional MC-CDMA system with combining process. To verify the merits of the new algorithm, the effect due to imperfect channel parameters estimation and frequency offset are investigated. We show that the proposed robust LCCM IQRD-RLS algorithm outperforms the conventional LCCM-gradient algorithm [6], in terms of output SINR, improvement percentage index (IPI), and bit error rate (BER) for MAI suppression under channel mismatch environment. Also, the performance of the WB MC-CDMA system is superior to the one with conventional MC-CDMA system. It is more robust to the channel mismatch and frequency offset. Moreover, the WB MC-CDMA system with robust LCCM IQRD-RLS algorithm does have better performance over other conventional approaches, such as the LCCM-gradient algorithm, maximum ratio combining (MRC), blind adaptation algorithm and partitioned linear interference canceller (PLIC) approach with LMS algorithm, in terms of the capability of MAI suppression and bit error rate (BER).

The conventional temporal filtering approach cannot be used to separate signal from interference which occupies the same temporal frequency band as signal. Using a spatial filtering at the receiver can separate signals from interference that originates from different spatial location. Many adaptive array beamforming algorithms, based on linear constraints, have been proposed for suppressing undesired interference and being applied to wireless communication systems for multiuser detection. The adaptive array system can be employed to automatically adjust its directional to achieve the purpose that nulls the interferences or jammers and thus, enhances the reception of the desired signal. Inverse QR Decomposition Recursive Least-square (IQRD-RLS) algorithm has many advantages such as where the LS weight vector be computed without back substitution, a well known numerical stable algorithm and offering better convergence rate, steady-state means-square error, and parameter tracking capability over the adaptive least mean square (LMS) based algorithms. In this thesis, a new application, GSC-IQRD-RLS combining Generalized Sidelobe Canceller (GSC) and IQRD-RLS algorithm, is developed. It preserves the advantages of GSC such as simple structure, less computations, and converts a linearly constrained optimization problem into a standard optimum filtering problem. But the performance is equivalent between GSC-IQRD-RLS and LC-IQRD-RLS algorithms.