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The problem of blind multiuser detection for an asynchronous multicarrier DS-CDMA system employing multiple transmit and receive antennae over a Rayleigh fading channel is considered in this paper. The solutions that we develop require prior knowledge of the spreading code of the user to be decoded only, while no further information either on the user to be decoded or on the other active users is required. Several combining rules for the observables at the output of each receive antenna are proposed and assessed, and the implications of the different options are studied in depth in terms of both detection performance and computational complexity. A closed form expression is also derived for the conditional error probability and a lower bound for the near-far resistance is provided. Results confirm that the proposed blind receivers can cope with both multiple access interference suppression and channel estimation at the price of a limited performance loss as compared to the ideal linear receivers which assume perfect channel state information.

The number of active users, their timing offsets, and their (possibly dispersive) channels with the access point are performance-critical parameters for wireless code division multiple access (CDMA). Estimating them as accurately as possible using as short as possible training sequences can markedly improve error performance as well as the capacity of CDMA systems. The fresh look advocated here permeates benefits from recent advances in variable selection and compressive sampling approaches to multiuser communications by casting estimation of these parameters as a sparse linear regression problem. Novel estimators are developed by exploiting two forms of sparsity present: the first emerging from user (in)activity, and the second from the uncertainty on user delays and channel taps. Simulated tests demonstrate a large gain in performance when sparsity-aware estimators of CDMA parameters are compared to sparsity-agnostic standard least-squares-based alternatives.