Golay complementary sequences and Reed-Muller codes based PAPR reduction for relay networks with superimposed training

Abstract

Thanks to relay network having the advantage of diversity and signal covering, lots of researches that require perfect channel estimation on relay network is undertaken. The superimposed training technique can estimate both the channel between source and relay and the channel between relay and destination pretty well. However, with orthogonal frequency division multiplexing (OFDM) being widely used, peak-to-average power ratio (PAPR) must be concerned. In this work, we apply a coding scheme based on Golay complementary sequences and Reed-Muller (RM) Codes into the system to reduce PAPR. Simulation results show that the proposed scheme does well in PAPR reduction.