Analysis of Precoder Decomposition Algorithms for MIMO System Design

Wireless communication over Multiple Input and Multiple Output (MIMO) channel achieve increased transmission rate by dividing the input stream into a multitude of parallel data streams which are transmitted in parallel. Precoding at the transmitter aims to decompose the channel into an uncorrelated multiple subchannels using the channel decomposition technique so that data streams will be sent in parallel independent subchannels. The proposed analysis is to analyze the performances of the MIMO precoder using various channel decomposition algorithms are compared and its computational complexity is analyzed. The channel decomposition schemes considered are Singular Value Decomposition, Geometric Mean Decomposition, LDLH, LU, Schur, QR and Jordan decomposition. The simulation and analytical results confirm that precoding for the MIMO channel decomposed by the QR scheme outperforms all the other precoding methods based on channel decomposition in the light of Bit Error Rate performance and involves a relatively lesser number of Floating Point Operations.

Automated summary

Wireless communication over Multiple Input and Multiple Output (MIMO) channel increases transmission rate by dividing the input stream into parallel data streams and transmitting them in parallel. The transmitter uses precoding to decompose the channel into independent subchannels using different channel decomposition algorithms. This analysis compares the performance and computational complexity of MIMO precoding using various channel decomposition algorithms. The results show that using the QR scheme for channel decomposition outperforms other precoding methods in terms of Bit Error Rate performance and requires fewer Floating Point Operations.