Research On Peak-to-average Ratio Suppression Technology Based On NC-OFDM System

OFDM is the best modulation technology with the best development prospects,and has been adopted by most wireless and wired communication standards.OFDM has a series of advantages.First of all,it has high spectrum utilization and anti frequency selective fading ability.It can eliminate the interference between symbols and recover the lost symbols due to the frequency selectivity of the channel.Therefore,it has certain error correction ability and high channel equalization and computational efficiency.However,the OFDM system also has a series of shortcomings.It requires high synchronization accuracy and must meet multipath propagation so that the orthogonality is not affected.Because the superposed peak power of all sub carrier signals is relatively large,it will produce high sidelobe,which may cause signal distortion.In order to make the signal more stable and fast transmission,how to effectively reduce the PAPR performance of OFDM system is the main research content of this paper.First of all,this article reduces the complexity of the algorithm and receiver without affecting the sidelobe suppression performance,and proposes a symbol-filled orthogonal frequency division multiplexing time domain algorithm,which inserts n consecutive OFDM correction symbols only in the guard interval,each OFDM symbol is seamlessly connected,thereby suppressing sidelobes.Analysis of the simulation results shows that the algorithm does not affect the sidelobe suppression performance,and is easy to implement,and its complexity is significantly lower than that of the inflexible OFDM system.Secondly,based on the non-continuous orthogonal frequency division multiplexing NC-OFDM model,this paper proposes a fusion optimization technology based on Selected Mapping(SLM)and Partial Transmit Sequence(PTS),and designs a system model of fusion technology.Through simulation comparison with other literature methods,it is verified that the SLM-PTS fusion technology has excellent peak to average power ratio(PAPR)reduction ability,but the algorithm implementation complexity is too high.Finally,this paper proposes a complementary SLM-Clipping fusion solution and PAPRnet model.The PAPRnet which uses the deep learning method to let the denoising autoencoder learn the constellation mapping and demapping of the symbols on each sub-carrier in NC-OFDM.Look for the mapping with the lowest PAPR value,and ensure that the original signal can be reconstructed by understanding the mapping.The simulation results verify that the algorithm has an excellent PAPR suppression effect on the NC-OFDM system,proves the effectiveness of the method,and greatly improves the computational efficiency.