Computationally Efficient Blind Source Separation-Based MIMO-PA Linearization

Abstract

This paper presents a Cross-Interference Reduction Digital predistortion (CIR-DPD) for a multiple-input and multiple-output (MIMO) system. The proposed method cancels the detrimental effect of crosstalk due to different MIMO branches and the antenna reflection from the same antenna. This technique incorporates an Independent Component Analysis (ICA) algorithm-based source separation technique to find the mixing matrix developed due to crosstalk and antenna reflection. Further, this mixing matrix is used to predict the pre-cancellation of antenna reflection and crosstalk matrix. The proposed CIR-ICA model furnishes a two-step single-iteration digital mitigation solution to multiple branches of MIMO transmitters. Compared to current DPD techniques, the proposed CIR-DPD model enables suitable detection for transmitter defects while lowering its complexity. The experimental proof-of-concept for the $4\times 4$ MIMO transmitter is presented in the presence of crosstalk, PA nonlinearity, and antenna reflection.

Keywords

• Crossover memory polynomial
• digital predistortion (DPD)
• independent component analysis
• multiple input multiple outputs
• normalized mean square error