Hybrid Rate-Splitting and Sparse Code Multiple Access (RS-SCMA): Design and Performance

This paper proposes, for the first time, a hybrid multiple access framework that integrates the principles of rate-splitting (RS) and sparse code multiple access (SCMA) in an SISO downlink scenario. The proposed scheme, termed RS-SCMA, unifies the powerful interference management capability of rate-splitting multiple access (RSMA) with the near-optimal multiuser detection of SCMA. A key feature of RS-SCMA is a tunable splitting factor $α$, which governs the allocation between the generic $M$-ary modulated common messages and SCMA-encoded private messages. This enables dynamic control over the fundamental trade-off between system sum-rate, bit error rate (BER), and the overloading factor. We develop novel transmitter and receiver architectures based on soft successive interference cancellation (SIC), incorporating message passing algorithm (MPA) detection and soft-symbol reconstruction. Furthermore, a unified analytical expression for the achievable sum-rate is derived as a function of the splitting factor $α$. The performance of the proposed RS-SCMA system is evaluated in terms of both BER and sum-rate. Simulation results confirm the superiority of RS-SCMA over conventional SCMA and multi-carrier RSMA, demonstrating its scalability and robustness even in the presence of channel estimation errors.

💡 Research Summary

The paper introduces RS‑SCMA, the first hybrid multiple‑access scheme that jointly exploits Rate‑Splitting Multiple Access (RSMA) and Sparse Code Multiple Access (SCMA) in a single‑input‑single‑output (SISO) downlink. The core idea is to superimpose a conventional M‑QAM‑modulated common stream with SCMA‑encoded private streams. A tunable splitting factor α (0 ≤ α ≤ 1) determines how many bits of the total payload N are allocated to the common stream (lc = αN) and to the private SCMA streams (lp = (1‑α)N). By varying α, the system can trade off between spectral efficiency, bit‑error‑rate (BER) performance and the overload factor λ = J/K (users per subcarrier).

The transmitter constructs each subcarrier signal as the sum of a common QAM symbol and a set of sparse codewords drawn from user‑specific SCMA codebooks. The authors derive analytical relationships linking α, λ, and the achievable sum‑rate. Under perfect successive interference cancellation (SIC) the sum‑rate is expressed as R_sum(α) = α·log₂M_c + (1‑α)·log₂M_p·λ, where M_c is the QAM order and M_p the SCMA codebook size. For imperfect SIC, a residual interference term ϵ is introduced, leading to a modified rate expression that quantifies performance loss.

Two receiver architectures are proposed. Rx‑1 targets low complexity: it extracts log‑likelihood ratios (LLRs) from the QAM demodulator, performs soft SIC on the common stream, and then runs the standard message‑passing algorithm (MPA) on the residual signal to detect all private SCMA messages. Rx‑2 is designed for coded systems; after an initial soft SIC, the channel decoder provides refined soft bits that are fed back to improve SIC accuracy, creating an iterative decoder‑assisted loop. Complexity analysis shows Rx‑1 scales as O(J·M·d_f) (J users, M codebook size, d_f subcarrier degree), while Rx‑2 adds modest decoder overhead but achieves significantly lower BER.

The paper also examines the impact of channel state information at the receiver (CSIR) errors by modeling estimation inaccuracies as an additive Gaussian error and applying a stochastic error model. Simulation results cover a range of α values, overload factors, and CSIR error levels. Across all scenarios, RS‑SCMA consistently outperforms conventional SCMA and multi‑carrier RSMA in terms of BER, block error rate (BLER), and achievable sum‑rate. The results highlight that α acts as a “knob” allowing system designers to balance throughput against reliability, especially in heavily overloaded regimes where traditional MA schemes struggle.

In conclusion, RS‑SCMA provides a unified framework that merges the interference‑management capabilities of RSMA with the near‑optimal multi‑user detection of SCMA. It offers a flexible degree of freedom (α) to adapt to varying network loads and quality‑of‑service requirements, making it a promising candidate for future 6G and beyond networks that demand massive connectivity, high spectral efficiency, and robust performance under imperfect channel knowledge. Future work suggested includes extending the design to MIMO scenarios, developing dynamic α‑optimization algorithms, and validating the concept on hardware testbeds.