International Journal of Wireless and Microwave Technologies (IJWMT)
IJWMT Vol. 16, No. 3, 8 Jun. 2026
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Regularized ZF and ML Fusion for Robust 6G THz UMIMO Systems: A Low-Complexity Approach with Enhanced BER Performance
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Author(s)
Index Terms
6G, Ultra-Massive MIMO (UM-MIMO), Hybrid Equalization. Regularized Zero-Forcing (RZF). Maxi-mum Likelihood (ML) Detection. Minimum Mean Square Equalization (MMSE), Bit Error Rate (BER)
Abstract
The development of sixth-generation (6G) terahertz (THz) wireless systems requires equalization techniques that can effectively handle severe channel impairments while maintaining low computational complexity. In this work, we propose a hybrid equalization framework that fuses regularized zero-forcing (ZF) with maximum likelihood (ML) refinement for ultra-massive multiple-input multiple-output (UM-MIMO) systems. The proposed Regularized ZF and ML Fusion (RZF-ML) equalizer leverages a regularization factor to mitigate noise enhancement and ill-conditioned channel effects, followed by a lightweight ML-based candidate search that refines symbol detection. This design provides a trade-off between the simplicity of linear equalizers and the optimality of ML detection. Simulation results under Rayleigh and Rician fading channels with high-order quadrature amplitude modulation (QAM) demonstrate that the RZF-ML equalizer achieves significantly improved bit error rate (BER) performance compared to conventional ZF and minimum mean square error (MMSE) equalizers, while approaching ML detection accuracy at a fraction of its complexity. The findings suggest that the proposed method is a promising candidate for robust equalization in 6G THz UM-MIMO networks, enabling reliable high-capacity communication in challenging propagation environments.
Cite This Paper
Mizanul Hoque, A.H.M. Asadul Huq, "Regularized ZF and ML Fusion for Robust 6G THz UMIMO Systems: A Low-Complexity Approach with Enhanced BER Performance", International Journal of Wireless and Microwave Technologies(IJWMT), Vol.16, No.3, pp. 172-181, 2026. DOI:10.5815/ijwmt.2026.03.12
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