PAPR and MUI reduction using novel Bayesian approach in OFDM based MIMO

We present a novel Bayesian approach for diminution of high peak-to-average power ratio (PAPR), one of the challenging issue of orthogonal frequency-division multiplexing (OFDM) in large-scale multiple-input multiple-output (MIMO) communication systems. The Bayesian approach models the problem into a hierarchical truncated Gaussian mixture prior (TGM). A variational expectation-maximization (EM) tactic is used to obtain an estimate of the hyperparameters. A generalized approximate message passing (GAMP) is incorporated to reduce the complexity of computation. Simulation result shows reduction in PAPR and cancelation of multi user interference (MUI), hence there is a noteworthy improvement in both power efficiency and performance of the system compared to previous stages.