PCA data reduction for MIMO based channel, capacity enhancement using 16-QAM modulation

Abstract

In the Modern Wireless Communication Systems, there is a direct need for the enhancement of the network capacity, in order to support more and more data. This paper describes the data reduction methodology for enhancement of channel capacity based on Principal Component Analysis (PCA) of the Multiple-Input-Multiple-Output (MIMO) based untether communication system. The communication system has employed 16 Quadrature Amplitude Modulation (16-QAM) scheme with LDPC for channel coding method for error correction. The proposed method here utilizes the Principal Component Analysis (PCA) for data reduction which transmits only the feature vectors i.e. Eigen Vector for the set of composite data for large numbers of signals data over time-stamped. The effectiveness of the proposed work is evident through the simulation results of the systems incorporating 1x1, 2x2, 3x3, 4x4 MIMO networks. We have presented RMSE analysis for the PCA regression for verification of the signal fidelity and the BER for confirmation of the recovery of the data over MIMO channel over LDPC coding. Here we observe that our proposed work has achieved much better results.