Research On Papr Reducing Algorithm In FBMC/OQAM System

Recently,the filter bank multicarrier with offset quadrature amplitude modulation(FBMC/OQAM)has attracted wide attention.Peak to Average Power Ratio(PAPR)is a common problem in the multi-carrier communication system.Not only the signal superposition,the shift of the real and imaginary part of the signal,but adjacent data blocks have an impact on PAPR.As a result,most reduction algorithms designed for OFDM are inapplicable to FBMC/OQAM system.Aiming at PAPR suppression schemes for FBMC/OQAM systems are few and existing some problems.So this thesis mainly research on PAPR reducing algorithm in FBMC/OQAM system.The main researches are as follow:Aiming at the existing algorithms based on the Partial Transmit Sequence(PTS)algorithm for FBMC/OQAM signal are all with a high complexity.In this thesis,we introduce a new PTS algorithm with dual layered phase sequencing(D-PTS)by improving traditional PTS algorithm.This algorithm groups the separated subsequences again based on traditional PTS,forming the dual layered frame of subsequence.Firstly,each block of FBMC/OQAM signal is divided into V subsequences according to the traditional PTS algorithm,and then the V subsequences are divided into D groups,each group contains V/D subsequence.Secondly,search phase sequences in different layer.The purpose of the underlying algorithm is to reduce the PAPR of the data block,while the top algorithm is to deal with the impact of adjacent data blocks.This method can reduce PAPR of the FBMC/OQAM signal with a low complexity and non-signal distortion.Theoretical analysis and numerical simulations confirm the performance of this algorithm.Aiming at the existing algorithms based on the Tone Reservation(TR)for FBMC/OQAM signal are not perform well.In this thesis,the model of subcarrier reservation in FBMC/OQAM system is constructed,and basing on the the essential reason of the high PAPR in FBMC/OQAM system,we introduce a self-adaptive circulation iterative tone reservation(SACI-TR)algorithm in combination with the signal structure characteristics.This algorithm can adaptively adjust the iterative threshold and the recursive convergence factor by adaptively learning the input data.The PAPR of the FBMC/OQAM signal is reduced in a small number of iterations,which not cause signal distortion.Further,this algorithm can enter convergence in fewer iterations,reducing the complexity of the system at another level.Theoretical analysis and numerical simulations confirm the performance of this algorithm.