Abstract-It is known that in an OFDM system using Hadamard transform or phase alteration before the IDFT operation can reduce the Peak-to-Average Power Ratio (PAPR). Both these techniques can be viewed as constellation precoding for PAPR reduction. In general, using non-diagonal transforms, like Hadamard transform, increases the ML decoding complexity. In this paper we propose the use of block-IDFT matrices and show that appropriate block-IDFT matrices give lower PAPR as well as lower decoding complexity compared to using Hadamard transform. Moreover, we present a detailed study of the tradeoff between PAPR reduction and the ML decoding complexity when using block-IDFT matrices with various sizes of the blocks.
Use of precoding transforms such as Hadamard Transforms and Phase Alteration for Peak to Average Power Ratio (PAPR) reduction in OFDM systems are well known. In this paper we propose use of Inverse Discrete Fourier Transform (IDFT) and Hadamard transform as precoding transforms in MIMO-OFDM systems to achieve low peak to average power ratio (PAPR). We show that while our approach using IDFT does not disturb the diversity gains of the MIMO-OFDM systems (spatial, temporal and frequency diversity gains), it offers a better trade-off between PAPR reduction and ML decoding complexity compared to that of the Hadamard transform precoding. We study in detail the amount of PAPR reduction achieved for the following two recently proposed full-diversity Space-Frequency coded MIMO-OFDM systems using both the IDFT and the Hadamard transform: (
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.