PAPR analysis of superimposed training based SISO/MIMO-OFDM systems with orthogonal affine precoder

Abstract

Superimposed training (ST) is used to estimate channel in orthogonal frequency division multiplexing (OFDM) systems which results in higher throughput than the time/frequency multiplexed training schemes. Orthogonal affine precoders (OAP) are used in ST-based SISO/MIMO-OFDM system to cancel the interference caused due to simultaneous data transmission. We analyze the peak to average power ratio (PAPR) of SISO/MIMO-OFDM systems which use OAP-based ST scheme. We show that the OAP-based ST scheme has higher PAPR than the conventional OFDM (without OAP-based ST) systems. We design an OAP using Zadoff–Chu (ZC) sequence, which has lower PAPR than the conventional OAPs. We further reduce the PAPR of the ST systems using selective mapping (SLM), but by increasing the system complexity. We show that the PAPR of the ST-based SISO/MIMO-OFDM systems with ZC-based OAP and SLM is identical to that of the conventional OFDM using SLM.