Enhancing transmitter efficiency for 5G MIMO Beamforming Application

Digital predistortion is a well-known technique used in communication systems to improve the efficiency and linearity of power amplifiers. However, the high-dimensional nature of MIMO Beamforming systems makes it challenging to implement digital predistortion algorithms in real time. To overcome this challenge, the paper implements several dimension reduction techniques, including independent component analysis (ICA), principal component analysis (PCA), compact singular vector decomposition (CSVD), and partial least square (PLS). The authors evaluate the performance of these techniques based on the reduction in computational complexity and the preservation of system performance metrics such as adjacent channel power ratio (ACPR) and normalized mean square error (NMSE). The results show that all the dimension reduction techniques can reduce the computational complexity of the digital predistortion algorithm. The authors also compare the tradeoffs between the computational complexity reduction, numerical stability, and the preservation of system performance metrics for each technique. Overall, the study concludes that dimension-reduction techniques can effectively reduce the computational complexity of digital predistortion algorithms in MIMO Beamforming systems. However, the selection of the technique should be based on the specific performance requirements of the system.