Research On The Equalization Algorithm For MIMO OFDM Downlink Systems

As the development of the intelligent mobile terminals and multimedia service,the demand on wireless communication of people is increasing rapidly,demand for higher transmission speed,better communication quality,and massive user access.The spectrum resource is very limited,the available spectrum resource has been scarcer and scarcer.Therefore,the improvement of the spectrum resources efficiently becomes more and more important.Multi-antenna technology can not only exploit the multi-path fading,but also improve the spectral efficiency,and is the inevitable developing trend of the current or future communication.In the MIMO OFDM downlink wireless communication system,when orthogonal frequency division multiplexing(OFDM)is combined with multiple-input multiple-output(MIMO),inter-symbol interference can be eliminate effectively.Moreover,when the channel state information is available in the base station,the transmit signals by the pre-processing will increase system throughout and capacity,and then improve the reliability of signal transmission.The interference problem of the wireless communication technology has been the core issue of concern.Multiple antenna technology and multi-user scenarios in the MIMO OFDM downlink wireless communication system,also face all kinds of the interference.The equalization technology is studied worldwide,which has theoretical and practical significance.In the MIMO OFDM downlink multiple antennas system,the existing serial equalization algorithm has high complexity and long process delay,and it is not conducive to practical application,meanwhile,the parallel equalization algorithm has poor performance,but the parallel equalization algorithm has the advantages of simple structure.So,low-complexity high-performance equalization technology becomes the new needs.Therefore,to solve some problems in current methods of equalization technology,this paper researches equalization technology for single user synchronization system model,single user asynchro-nous system model and multi-user system model.This paper mainly includes:Firstly,the equalization method for single user synchronization system model in the MIMO OFDM downlink is researched.Based on soft iterative LMMSE equalization model,a hybrid iterative equalization algorithm based on precoding matrix.The main idea of the proposed algorithm is to reduce the effects of deep-fading channel to transmit signal and reduce the algorithm complexity,the influence of part of subcarrier which affected by deep fading on the original transmitted signal has been decreased by the idea of precoding.Meanwhile,the minimum mean square error(MMSE)ordered QR decomposition method is introduced to reduce the complexity of the traditional LMMSE soft iterative equalization algorithm,thereby achieving high performance with low computational complexity.It is worth noting that the complexity of the proposed algorithm compared with soft iterative equalization scheme based on LMMSE has been reduced obviously in receiving antenna than or equal to the transmitting antenna,but the complexity of the proposed algorithm faces exponential growth with the number of antenna size,the length of channel coding and the different modulation,which is limited in the actual communication process.Therefore,in order to further reduce the complexity of equalization algorithms to meet the requirements of actual communication,and based on soft parallel iterative equalization model,two kinds of parallel iterative equalization methods have been proposed,including the parallel iterative equalization algorithm based on precoding extension and modified matrix,respectively.The first proposed algorithm by the idea of precoding expand and minimum mean square error sorting QR decomposition method,can significantly relieve the impact of the error propagation of traditional parallel iterative equalization algorithm,and effectively reduce the computing complexity,so as to contributing an adjustable tradeoff between the system performance and complexity.The second equalization algorithm by introduction of the modified matrix,which is basis on the result of the first equalization algorithm,can effectively solve the situation which the first algorithm regards part of the desired signal as interference,thereby the bit error rate(BER)performance will be further improved.Secondly,the equalization method for single user asynchronous system model in the MIMO OFDMdownlink is researched.Current asynchronous parallel iterative equalization method has some problems,such as only considering the interference between various antennas,neglecting the error propagation problem in the iteration process,and only considering detection accuracy,neglecting computational complexity.To solve those problems,two parallel iteration equalization methods are proposed,including parallel iterative equalization method based on power extension and parallel iterative equalization method based on modified matrix.They solve some kinds of interference in the current asynchronous communication system by power extension matrix and modified matrix,respectively.So as to contributing an adjustable tradeoff between the system performance and complexity.And their performances and complexities are detailed analyzed.Two parallel equalization method fully considers the antenna interference,error propagation and computing complexity.They can overcome the shortcomings of current asynchronous equalization methods which only consider one or two kinds of interference,and optimal determine equalization scheme to improve the system BER performance and reduce the influence of various interference to transmission signal.Finally,the equalization method for multi-user synchronization system model in the MIMO OFDM downlink is researched.Using the idea of diry paper coding(DPC)and pre-processing matrix,a successive singal-to-leakage-plus-noise ratio(SSLNR)algorithm based on pre-processing matrix is proposed for multi-user MIMO system.The main idea of DPC cancelled the known leakage of other users at the transmitter.Therefore,when SLNR is calculated,algorithm only consider the unknown leakage of other users,ignore the known leakage.And then precoding matrix are obtained by maximizing SLNR.The main idea of pre-processing matrix by maximizing the system capacity,reduce the nonlinear operation to the effect of system performance and capacity.To maximize the system capacity,the pre-processing matrix is calculated,it can effectively reduce the performance and capacity loss which caused by the nonlinear modulo operation.After the precoding matrix and pre-processing matrix are obtained,Tomlinson-Harashima precoding(THP)is applied to cancel the known leakage which are ignored in the SLNR calculation.The proposed algorithm can improve the BER performance compared with the current SSLNR scheme based on precoding for multi-user MIMO.Meanwhile,the number of antennas is not strictly limited.In order to further improve performance,SSLNR precoding algorithm based on pre-processing matrix and geometric mean decomposition(GMD)for multi-user MIMO is proposed.SSLNR precoding algorithm based on pre-processing matrix and geometric mean decomposition exists gian gap between data streams as the original SSLNR precoding algorithm.The BER performance is mainly determined by the worst sub-channel,there cause a big performance loss.To solve this problem,the idea of GMD is used,GMD method is applied to SSLNR algorithm based on pre-processing matrix,the gian gap of data steams of each user is decreased,and then the fairness among users is improved,so as to enhance the BER performance.