Multi-User SR-LDPC Codes via Coded Demixing with Applications to Cell-Free Systems

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.