Comparative Analytical Study of SCMA Detection Methods for PA Nonlinearity Mitigation.

Area of Science:

• Wireless communication systems
• Signal processing
• Information theory

Background:

• Non-orthogonal Multiple Access (NOMA) enables multiplexing users over limited resources.
• Sparse Code Multiple Access (SCMA) offers coding gain and optimal detection via Message Passing Algorithm (MPA).
• Nonlinear power amplifiers degrade SCMA bit error rate (BER) performance.

Purpose of the Study:

• To analytically investigate the error-floor performance of Bussgang-based MPA detectors in SCMA systems.
• To compare the error-floor performance of Bussgang-based MPA with a Reproducing Kernel Hilbert Space (RKHS)-based MPA using Random Fourier Features (RFF).
• To quantify the BER performance gap between the two detector types.

Main Methods:

• Analytical derivation of the error-floor for Bussgang-based MPA.
• Implementation and simulation of RKHS-based MPA using RFF.
• Comparative analysis of BER performance through simulations and analytical results.

Main Results:

• Bussgang-based MPA achieves a higher error floor compared to RKHS-based MPA.
• RKHS-based MPA demonstrates superior BER performance, mitigating nonlinear amplifier effects more effectively.
• The performance gap and error floor are analytically quantified and validated by simulations.

Conclusions:

• RKHS-based MPA, particularly with RFF, is a more effective solution for mitigating nonlinear amplifier-induced degradation in SCMA systems.
• While computationally simpler, Bussgang-based MPA exhibits a higher BER floor, limiting its applicability in performance-critical scenarios.
• The study provides crucial analytical insights for designing robust SCMA systems operating under nonlinear conditions.