The Research On Reducing PAPR Of MIMO-OFDM System

Multiple-Input Multiple-Output(MIMO) technology fully develops spatial resources by using multiple antennas to realize multiple input and multiple output.It can highly enhance the channel capacity without increasing spectral resources and the transmit power of antennas.Orthogonal Frequency Division Multiplexing(OFDM) technology is a multi-carrier narrow-band transmission,whose subcarriers are orthogonal,can make use of frequency spectrum resources efficiently.Taking full advantage of time,frequency and space diversity,the combination of MIMO and OFDM can increase the tolerance of wireless communication systems to noise, interference and multipath.MIMO-OFDM has become a promising candidate for high performance 4G broadband wireless communications because of its potential for achieving higher data rate and providing more reliable reception performance.There is a prohibitively large Peak-to-Average Power Ratio(PAPR) of MIMO-OFDM for its multi-carrier modulation.When signal through non-linear devices,such as power amplifiers,it requires the amplifier with a large dynamic range, or it will result in a nonlinear distortion and spectral growth of OFDM signals in the form of inter-channel interference and out-of-band radiation,greatly reduces the performance of MIMO-OFDM systems.High PAPR makes many restrictions to practical application of MIMO-OFDM.It is therefore necessary to research on PAPR reduction methods for MIMO-OFDM.PAPR reduction algorithms for MIMO-OFDM systems are researched in this paper,and the main innovations and contributions are as follows:Firstly,the representative algorithms such as Selective Mapping(SLM) method and Partial Transmit Sequence(PTS) method are analysed,and the improved methods named concurrent SLM(CSLM) and concurrent PTS(CPTS) are proposed to reduce the high complexity of independent SLM(ISLM) and independent PTS(IPTS) by exploiting the characteristics of MIMO-OFDM systems and investigating the two antennas have the same PAPR of Space Time Block Code(STBC) MIMO-OFDM systems.MATLAB simulation proves that the proposed CSLM and CPTS have similar performance as ISLM and IPTS separately,but almost half of the computational complexity can be reduced.Secondly,a novel method to reduce PAPR of MIMO-OFDM systems is proposed.This method applies space and frequency two-dimensional subblock permutation and inversion to MIMO-OFDM signals based on STBC,makes full use of additional freedom degrees provided by space and frequency dimension.Three suboptimal schemes,termed successive suboptimal SFPI(SS-SFPI), successive-random suboptimal SFPI(SRS-SFPI) and random suboptimal SFPI (RS-SFPI) are presented to reduce the complexity of the proposed scheme.Then the autocorrelation properties of Constant Amplitude Zero Auto Correlation(CAZAC) sequence is proofed,and CAZAC matrix transform is introduced to reduce PAPR. Joint SFPI and CAZAC algorithm is proposed to further reduce PAPR.Simulation results show that these proposed methods can provide better PAPR reduction performance than Cross-Antenna Rotation and Inversion(CARI),and the suboptimal schemes can significantly reduce PAPR on all transmit branches simultaneously with low complexity.Finally,considering the time degrees of freedom in a practical system with multiple symbols in a timeslot structure are not extensively studied and used for reduction of PAPR,a new algorithm termed as Space-Time-Frequency Permutation and Inversion(STFPI) is proposed based on taking full advantages of three-dimensional degrees of freedom in space,time and frequency.And a suboptimal scheme,that is,random suboptimal Space-Time-Frequency Permutation and Inversion(RS-STFPI),is introduced to decrease the system complexity with little side information.Simulation results show that the proposed schemes can significantly reduce PAPR for MIMO-OFDM systems with limited complexity.