Symbol Error Analysis of Linear Receivers in Terahertz Channels under Channel-Noise Dependence

This paper develops a comprehensive framework for the performance analysis of linear detectors, namely zero-forcing (ZF) and minimum mean-square error (MMSE), under diverse terahertz (THz) channel conditions. Three fading models are considered: Rayleigh fading, the $α$--$μ$ distribution for indoor THz environments, and the mixture-gamma (MG) distribution for outdoor THz scenarios. Semi-analytical, approximate, and asymptotic expressions for the symbol error rate (SER) are derived, explicitly incorporating the correlation between the channel and the additive noise arising from hardware impairments. This correlation is characterized using both statistical approaches and copula-based methods to effectively capture complex dependency structures. The theoretical findings are validated through simulations, demonstrating strong agreement with the derived expressions and confirming the accuracy and robustness of the proposed framework. The results demonstrate the significant impact of channel--noise dependence on THz-band receiver performance and verify the expected performance degradation of biased MMSE receivers in point-to-point links employing higher-order quadrature amplitude modulation. Specifically, at a target SER of $10^{-3}$, a 70\% correlation results in approximately a 6.5~dB degradation in the effective signal-to-noise ratio, with mismatched MMSE detection incurring an additional 1~dB loss compared to ZF. Nonetheless, MMSE offers enhanced numerical stability under severe channel fading conditions, where channel inversion causes noise amplification.

Diversity Analysis for Indoor Terahertz Communication Systems under Small-Scale Fading

Harnessing diversity is fundamental to wireless communication systems, particularly in the terahertz (THz) band, where severe path loss and small-scale fading pose significant challenges to system reliability and performance. In this paper, we present a comprehensive diversity analysis for indoor THz communication systems, accounting for the combined effects of path loss and small-scale fading, with the latter modeled as an $\alpha-\mu$ distribution to reflect THz indoor channel conditions. We derive closed-form expressions for the bit error rate (BER) as a function of the reciprocal of the signal-to-noise ratio (SNR) and propose an asymptotic expression. Furthermore, we validate these expressions through extensive simulations, which show strong agreement with the theoretical analysis, confirming the accuracy and robustness of the proposed methods. Our results show that the diversity order in THz systems is primarily determined by the combined effects of the number of independent paths, the severity of fading, and the degree of channel frequency selectivity, providing clear insights into how diversity gains can be optimized in high-frequency wireless networks.