Indirectly estimated adaptive detectors for code-division multiple-access signals

This paper presents the development of indirectly estimated adaptive (IDEA) detectors for code-division multiple-access (CDMA) signals in wireless communication systems. Multiuser CDMA detection is formulated as an inverse problem in the presence of noise, and the estimation of the detector parameters is accomplished using elements of regularization theory. The development of autonomous CDMA detectors that are capable of adjusting to the channel characteristics with the support of training sequences relies on data-dependent procedures designed to reduce the effect of noise and interfering users on the performance of the detector. The detector parameters can be computed by adaptive algorithms that require no matrix inversion. The proposed IDEA detector is evaluated and compared with existing multiuser CDMA detectors in terms of their robustness to noise, resistance to the near-far problem, and ability to handle multipath signals.