In this paper we design novel generalized likelihood ratio test (GLRT)-type packet-data detectors for general multiaccess/multiuser digital communication systems and we develop analytical performance evaluation tools for finite data packet sizes. For the known channel case, we derive a coherent GLRT packet-data detector while for the unknown channel case we derive both a coherent pilot assisted GLRT packet-data detector and a differential phase-shift-keying (DPSK) GLRT packet-data detector. Efficient suboptimum implementations of the above schemes that exhibit complexity linear in the packet size are also considered. Simulation studies evaluate the performance of the proposed schemes in the context of packet-data code-division multiple access (CDMA) communications.

In this paper we propose novel generalized likelihood ratio test (GLRT) packet-data detectors for general multiaccess/multiuser digital communication systems and we develop analytical performance evaluation tools for finite data packet sizes. We evaluate the performance of the proposed GLRT schemes in the context of packet-data CDMA communications.

When the auxiliary vector (AV) filter generation algorithm utilizes sample average estimated input data statistics, it provides a sequence of estimates of the ideal minimum mean-square error or minimum-variance distortionless-response filter for the given signal processing/receiver design application. Evidently, early nonasymptotic elements of the sequence offer favorable bias/variance balance characteristics and outperform in mean-square filter estimation error the unbiased sample matrix inversion (SMI) estimator as well as the (constraint) least-mean square, recursive least-squares, "multistage nested Wiener filter", and diagonally-loaded SMI filter estimators. Selecting the most successful (in some appropriate sense) AV filter estimator in the sequence for a given data record is a critical problem that has not been addressed so far. We deal exactly with this problem and we propose two data-driven selection criteria. The first criterion minimizes the cross-validated sample average variance of the AV filter output and can be applied to general filter estimation problems; the second criterion maximizes the estimated J-divergence of the AV filter output conditional distributions and is tailored to binary phase-shift-keying-type detection problems.