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Is successive interference cancellation (SIC) decoding always the optimal choice in non-orthogonal multiple access (NOMA) systems? While the answer is positive based on Shannon theory, which is applicable to infinite-length codewords drawn from a Gaussian distribution, this may not universally hold for systems with finite-alphabet inputs. Specifically, in this paper, we demonstrate that for quadrature amplitude modulation (QAM)-based NOMA, SIC decoding fails for certain values of power allocation coefficient a:, used to divide power among NOMA users. With this observation, we propose employing maximum likelihood (ML) detection to decode QAM-NOMA. While SIC decoding for QAM-NOMA requires allocating higher power to the user with a weaker channel to prevent symbol crossing in super-constellations, ML detection can successfully handle a broader range of power allocation coefficients. We then derive closed-form symbol error rates for quadrature phase shift keying-based NOMA systems across any a: and validate them through simulations. The results demonstrate the effectiveness of ML detection, particularly in scenarios where SIC decoding fails. 

A deep autoencoder (DAE)-based structure for end-to-end communication over the two-user Z-interference channel (ZIC) with finite-alphabet inputs is designed in this paper. The proposed structure jointly optimizes the two encoder/decoder pairs and generates interference-aware constellations that dynamically adapt their shape based on interference intensity to minimize the bit error rate (BER). An in-phase/quadrature-phase (I/Q) power allocation layer is introduced in the DAE to guarantee an average power constraint and enable the architecture to generate constellations with nonuniform shapes. This brings further gain compared to standard uniform constellations such as quadrature amplitude modulation. The proposed structure is then extended to work with imperfect channel state information (CSI). The CSI imperfection due to both the estimation and quantization errors are examined. The performance of the DAE-ZIC is compared with two baseline methods, i.e., standard and rotated constellations. The proposed structure significantly enhances the performance of the ZIC both for the perfect and imperfect CSI. Simulation results show that the improvement is achieved in all interference regimes (weak, moderate, and strong) and consistently increases with the signal-to-noise ratio (SNR). For instance, more than an order of magnitude BER reduction is obtained with respect to the most competitive conventional method at weak interference when SNR>15dB and two bits per symbol are transmitted. The improvements reach about two orders of magnitude when quantization error exists, indicating that the DAE-ZIC is more robust to the interference compared to the conventional methods.