Parallelly Processed Peak Cancellation Signal-Based PAPR Reduction Method Using Null Space in MIMO Channel for MIMO-OFDM Signals

In this paper, we propose a computational complexity-efficient algorithm called PCCNC for the adaptive peak-to-average power ratio (PAPR) reduction method using the null space in a multiple-input multiple-output (MIMO) channel for MIMO-orthogonal frequency division multiplexing (OFDM) signals. Based on our preliminary work, the proposed PCCNC in this paper newly introduces a parallel peak cancellation process at each iteration. By adding the multiple peak cancellation (PC) signals to the time-domain transmission signal vector simultaneously, the number of iterations in the iterative algorithm is reduced. The constraint so that the PC signal is transmitted only to the null space in the MIMO channel by beamforming (BF) makes interference from PC signal to the data streams not observed at the receiver side. Since the fast Fourier transform (FFT) and inverse FFT (IFFT) operations at each iteration are not required different from the conventional algorithm and thanks to the introduced parallel processing, the proposed PCCNC reduces the required number of iterations and total computational complexity compared to the conventional algorithm for achieving the same throughput-vs.-PAPR performance.