The Research Of Algorithm On PAPR Reduction In MIMO-OFDM Systems

MIMO-OFDM is a well-known and mature technology in 4G wireless communication systems because it can provide high data rate transmission capability,high bandwidth efficiency robustness,and high robustness against frequency selective fading.OFDM subcarriers can be dynamically allocated among multiple users,and by using MIMO technology,the spectral efficiency of the system can be improved,and the data transmission rate and link reliability can be improved by spatial diversity.MIMO configuration can also increase system capacity without increasing power and bandwidth.However,one of the major drawbacks of OFDM is the peak-to-average power ratio(PAPR)caused by the inverse Fourier transform used in this scheme,especially when the number of sub-carriers increased.The high PAPR problem will lead to signal distortion,spectrum expansion,and system performance degradation,which is common in systems based on OFDM modulation.Therefore,how to effectively reduce PAPR has become a research hotspot for systems based on OFDM modulation.Considering the high PAPR problem,the operating point of the transceiver power amplifier needs to have power back-off to adapt to the fluctuation of the signal power and prevent it from operating in a non-linear region.Nonlinearity creates mutual interference between subcarriers and distorts the signals,which increases the bit error rate.Therefore,the power amplifier should work in the linear region as much as possible to avoid signal distortion of the highest peak,thereby reducing the power efficiency of the entire system.OFDM subcarriers can be dynamically allocated among multiple users,and spectrum efficiency can be improved by using MIMO technology.In fact,high PAPR reduces the efficiency of battery life,and power efficiency is a major concern for portable devices.Therefore,it is important to reduce the high PAPR in OFDM signals.This paper studies the algorithm for reducing PAPR in MIMO-OFDM systems from three aspects.The specific work is as follows:(1)Describes the definition and statistical characteristics of PAPR in MIMO-OFDM systems;studies the difference of PAPR in discrete and continuous time domain of OFDM signals;analyzes the influence of oversampling rate and high power amplifier on PAPR;Three types of technologies for reducing PAPR are introduced.Finally,the description of the MIMO-OFDM system with space-frequency coding structure and its PAPR reduction are summarized.The above content is for the following research to design and effectively reduce the PAPR algorithm to provide basic theory and discussion.(2)The probabilistic technology reduces the PAPR by linearly transforming the transmitted signal,which is a technique that does not cause signal distortion and does not degrade the system's BER performance.Therefore,this paper mainly discusses Partial Transmit Sequences(PTS)in this type of technology.In this paper,a low-complexity PTS algorithm is proposed based on the existing PAPR reduction algorithm.In this method,the signal decomposition idea is applied to PTS,and the number of segmentation sub-blocks of the PTS is increased while the IFFT computation complexity is kept constant,and the PAPR performance of the PTS algorithm is improved;and the phase weighting factor between multiple antennas under the space-frequency coding reuse is provided.The conjugate conversion relationship reduces the IFFT calculation amount and the sideband information transmission amount of the transmitter PTS algorithm.Finally,the dual-layered search is used to reduce the computational complexity of the traversal search phase weighting factor in the PTS.(3)In order to solve the problem of higher computational complexity caused by traversal searching for the optimal phase weighting factor in the partial transmission sequence algorithm,a partial transmission sequence algorithm based on discrete firefly algorithm is proposed.Because of the discrete firefly algorithm that it has the characteristics of fewer parameters,fast convergence and easy implementation in solving the global optimization search problem,the process of searching the optimal phase weighting factor has been transformed into a global optimization search problem.The Euclidean distance is replaced with the Hamming distance by the discrete firefly algorithm.Based on this,the attraction function is improved so that it does not descend quickly due to the distance increased;the perturbation constant is replaced with the distance-dependent fuzzy function to make it self-adaptability.The above improvements can well expand the global search ability of the algorithm,improve the local convergence speed of the algorithm,and get the better search for optimal phase weighting factors.