# Deep Learning-based Codebook Design for Code-domain Non-Orthogonal Multiple Access Approaching Single-User Bit Error Rate Performance

arXiv: https://arxiv.org/abs/2104.00818 · HTML: https://mlsanity.com/paper/2104.00818/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Apr 2021.

## Built on by (most cited first, 3 of 3)

- [Modulation and Coding for NOMA and RSMA](https://mlsanity.com/paper/2410.00239/) (2024)
- [Data-aided Active User Detection with a User Activity Extraction Network for Grant-free SCMA Systems](https://mlsanity.com/paper/2205.10780/) (2022)
- [Learning Binary Autoencoder-Based Codes with Progressive Training](https://mlsanity.com/paper/2511.09221/) (2025)

## Abstract (arXiv)

A general form of codebook design for code-domain non-orthogonal multiple access (CD-NOMA) can be considered equivalent to an autoencoder (AE)-based constellation design for multi-user multidimensional modulation (MU-MDM). Due to a constrained design space for optimal constellation, e.g., fixed resource mapping and equal power allocation to all codebooks, however, existing AE architectures produce constellations with suboptimal bit-error-rate (BER) performance. Accordingly, we propose a new architecture for MU-MDM AE and underlying training methodology for joint optimization of resource mapping and a constellation design with bit-to-symbol mapping, aiming at approaching the BER performance of a single-user MDM (SU-MDM) AE model with the same spectral efficiency. The core design of the proposed AE architecture is dense resource mapping combined with the novel power allocation layer that normalizes the sum of user codebook power across the entire resources. This globalizes the domain of the constellation design by enabling flexible resource mapping and power allocation. Furthermore, it allows the AE-based training to approach a global optimal MU-MDM constellations for CD-NOMA. Extensive BER simulation results demonstrate that the proposed design outperforms the existing CD-NOMA designs while approaching the single-user BER performance achieved by the equivalent SU-MDM AE within 0.3 dB over the additive white Gaussian noise channel.