A Theoretical Performance Analysis Framework for Data Detection in the Terahertz Band

Abstract

Future wireless systems, particularly those operating in the terahertz (THz) band, require accurate channel modeling and analysis that move beyond classical assumptions of idealized fading and independent channel and noise. This thesis develops a unified analytical framework for evaluating the symbol error performance of THz-band linear detectors under realistic channel–noise dependencies and diverse fading conditions. The analysis spans Rayleigh, α - μ, and mixture–gamma (MG) channels, capturing both indoor and outdoor THz propagation environments. New semi-analytical, asymptotic, and approximation-based expressions are derived for zero-forcing (ZF) and minimum mean-square error (MMSE) detection, accounting for the bias and noise enhancement effects inherent to each scheme. The thesis also presents exact and approximate diversity analyses for maximum-ratio combining (MRC) in THz systems. Extensive simulations confirm the accuracy of the proposed framework. Overall, this work provides a comprehensive and tractable foundation for analyzing and optimizing next-generation THz communication links.