In the user identification (UI) scheme for a multiple-access fading channel based on a randomly generated (0, 1, -1)-signature code, previous studies used the signature code over a noisy multiple-access adder channel, and only the user state information (USI) was decoded by the signature decoder. However, by considering the communication model as a compressed sensing process, it is possible to estimate the channel coefficients while identifying users. In this study, to improve the efficiency of the decoding process, we propose an iterative deep neural network (DNN)-based decoder. Simulation results show that for the randomly generated (0, 1, -1)-signature code, the proposed DNN-based decoder requires less computing time than the classical signal recovery algorithm used in compressed sensing while achieving higher UI and channel estimation (CE) accuracies.

A recursive construction of (k+1)-ary error-correcting signature code is proposed to identify users for MAAC, even in the presence of channel noise. The recursion is originally from a trivial signature code. In the (j-1)-th recursion, from a signature code with minimum distance of 2j-2, a longer and larger signature code with minimum distance of 2j-1 is obtained. The decoding procedure of signature code is given, which consists of error correction and user identification.

A new pilot-aided multiuser detection scheme, single code cyclic shift (SCCS) detector, is proposed in this paper for synchronous CDMA multiuser signal reception. The unique feature of the proposed detector is that a receiver can decode multiuser signals even without explicit knowledge of all signature codes active in the system. The transmitting signal from a base station to a mobile contains two separated channels: the pilot and data channels; the former consists of periodically repeated pilot symbols encoded by the same signature codes as the one spreading the latter. Both pilot and data signals for a specific mobile are sent by a base-station using quadrature and in-phase carriers at the same frequency with QPSK modulation. A matched filter bank, consisting of M correlators that match to distinct cyclic-shifted versions of a "single" signature code, is employed for "channel cyclic shift correlation function" estimation, followed by the multiuser detection algorithm based on the channel information obtained earlier. The performance of the proposed SCCS detector is evaluated and compared to decorrelating detector by computer simulations considering various multipath channels with different profiles. The results demonstrate that a synchronous CDMA joint detection can be implemented successfully without necessarily knowing all signature codes of the system.