A Novel Domain Transformation Based on Iterative Rotation for Linear Time-Variant Fading Channels

An effective precoding method stands as an imperative task, for the dynamic fluctuations inherent in fading channels that have a huge impact on communication systems. This paper introduces a novel transformation method for constructing a domain based on rotation matrices, termed Iterative Rotation Orthogonal Transformation (IROT). Our method centers on investigating the key factor in determining symbol decision accuracy, which is the distribution of noise energy superimposed on each symbol within a symbol block. The optimal distribution is influenced not only by channel fading but also by the average signal-to-noise ratio (SNR). By employing linear equalization, we quantitatively evaluate the impact of the domain transformation method on noise energy distribution. When the SNR surpasses a specific threshold, the symbol error rate (SER) reaches its minimum through the average allocation of noise energy. To achieve controllable adjustments of the noise energy, IROT constructs a unitary matrix by a double-layer iteration. Then we calculate the SNR threshold and analyze the complexity and convergence of IROT. Furthermore, we proposed the inverse balanced IROT to improve the SER performance at low SNR. The simulation results show the superior SER performance of IROT compared to other domain transformation and pre-equalization methods.