  Novel sparse regression LDPC (SR-LDPC) codes exhibit excellent performance
over additive white Gaussian noise (AWGN) channels in part due to their natural
provision of shaping gains. Though SR-LDPC-like codes have been considered
within the context of single-user error correction and massive random access,
they are yet to be examined as candidates for coordinated multi-user
communication scenarios. This article explores this gap in the literature and
demonstrates that SR-LDPC codes, when combined with coded demixing techniques,
offer a new framework for efficient non-orthogonal multiple access (NOMA) in
the context of coordinated multi-user communication channels. The ensuing
communication scheme is referred to as MU-SR-LDPC coding. Empirical evidence
suggests that, for a fixed SNR, MU-SR-LDPC coding can achieve a target bit
error rate (BER) at a higher sum rate than orthogonal multiple access (OMA)
techniques such as time division multiple access (TDMA) and frequency division
multiple access (FDMA). Importantly, MU-SR-LDPC codes enable a pragmatic
solution path for user-centric cell-free communication systems with (local)
joint decoding. Results are supported by numerical simulations.
