Peak-to-average power ratio reduction technique for MIMO/OFDM systems

Convolutional coding has been classically used in channel coding to provide Forward Error Correction (FEC) capability to the system by adding some carefully designed redundant information to the data being transmitted through the channel. However, in this work, we use convolutional codes for a different purpose: the reduction of the Peak-to-Average Power Ratio (PAPR) in an Orthogonal Frequency Division Multiplexing (OFDM) system by utilising these codes as spreading codes. This is an alternative to turbo coding and Low-Density Parity Check (LDPC) codes, which have been used for the same purpose in our previous works. The PAPR is a major drawback in most multicarrier communication techniques such as OFDM. OFDM consists of lots of independent modulated subcarriers; as a result, the amplitude of such a signal can have very large values. These large peaks increase the amount of intermodulation distortion, resulting in an increase in the error rate. The PAPR of an OFDM signal can be reduced in several ways: Selective Mapping (SLM), Golay sequences, cyclic coding, clipping and filtering and multiple signal representation techniques. Our results show that using LDPC coding in mitigating PAPR led to a 6%-60% reduction in this ratio, which is better than our proposed work based on either turbo coding or convolutional coding and the SLM and clipping techniques in the literature.