Research On Transmit Precoding And Receive Filtering Techniques In Multi-User MIMO Networks

Wireless communication of the future will be committed to the technical application of "full coverage,full spectrum,full application,and strong security" to meet the communication needs of large-scale connection,high-reliability transmission and lowlatency guarantee,so as to effectively cope with the explosive growth of data volume,the massive access of communication equipments and the continuous emergence of new communication services.Multiple-input multiple-output(MIMO)technology is an important research topic in future wireless communication.With the help of multiplexing gain and diversity gain brought by multiple antennas,the spectral efficiency(SE)of communication system can be significantly improved.MIMO technology is a key enabling technology to meet the quality of service(QoS)and the quality of experience(QoE)for users of future wireless communication system.Transmit precoding and receive filtering in multi-user MIMO networks are the core issues in the design of MIMO transceivers.Reasonable design of transmit precoding matrix and receive filtering matrix can effectively suppress interference and greatly improve the transmission rate of system.However,the interference in multi-user MIMO networks is more complex,involving inter-user interference(IUI)and inter-stream interference(ISI),which can seriously affect the performance of the communication system.At the same time,the randomness of noise in the wireless transmission environment,the difference of user communication capabilities and the dynamic nature of communication requirements will affect the performance of the optimization algorithm of transmit precoding matrix and receive filtering matrix in multi-user MIMO networks.In a multi-user MIMO network,how to effectively suppress inter-user interference and inter-stream interference by designing scientific transmit precoding matrix and receive filtering matrix optimization algorithms,while avoiding the influence of randomness of noise,the differences in user communication capabilities and the impact of dynamic nature of communication requirements on algorithms’ performance remains to be further studied.The core issues of this thesis is:"How to effectively suppress the inter-user interference and the inter-stream interference in multi-user MIMO networks to improve the system transmission rate,and ensure that the transmit precoding matrix and the receive filtering matrix optimization algorithms can better adapt to the randomness of noise,differences in user communication capability and dynamic nature of communication requirements".We take the optimization of signal space dimensions and signal power as the core technical means,with automatic adjustment of the algorithm based on signal-tonoise ratio(SNR),automatic adjustment of algorithm based on user priority,inter-user interference and inter-stream interference comprehensive suppression and relay-assisted signal processing as technical aids.We focus on the research of transmit precoding and receive filtering techniques in multi-user MIMO networks,and design efficient MIMO transceiver optimization algorithms.The specific research contents and innovation points are briefly described as follows:1)For the scenario of MIMO broadcasting channel(BC)networks,by adopting interference suppression technology,a joint optimization mechanism of signal power and space dimensions is proposed,and the optimization algorithms of received signal power and space dimensions are designed by SNR adjustment at user level and stream level,respectively.The optimization algorithms solve the problem that the existing algorithms cannot automatically adapt to the randomly changing noise environment,and realize the comprehensive suppression of inter-user interference and inter-stream interference,as well as the automatic adjustment of algorithm according to the specific noise environment.Specifically,the optimization of signal power is used to counteract the influence of noise on system performance,the optimization of signal space dimensions is used to effectively suppress the interference,and the measurement standards of signal power and space dimensions are designed,respectively.At the same time,with the help of the automatic adjustment of weighting factor and adjustment factor,the algorithms can automatically adjust the optimized objective functions according to different SNR values,so that the algorithms can obtain higher performance in different noise environments.The simulation results show that the proposed algorithms can significantly improve the system performance of MIMO broadcasting channel networks in different signal-to-noise ratio(SNR)environments.2)For the scenario of asymmetric MIMO broadcasting channel networks,by adopting the specific user priority mode,a corresponding automatic adjustment mechanism is proposed,and a transceiver and power joint optimization algorithm based on user priority is designed to deal with the difference in user communication capabilities,as well as the problem of the dynamics of communication requirements,so that the automatic adjustment of algorithm is realized.Specifically,for a specific user priority mode,an adjustment matrix is designed,and this adjustment matrix is used to adjust the transmit precoding matrix,the receive filtering matrix and the power allocation vector,so that the focus of optimization algorithm tends to the user with high priority as much as possible.Simulation results show that the proposed algorithm can improve the transmission rate of users with high priority as much as possible.3)For the scenario of MIMO interference channel(IC)networks,by adopting the rank-constrained interference suppression technology,the interference leakage minimization mechanism at stream level is proposed,and the optimization algorithm based on the rank constraint at stream level is designed to solve the problem of comprehensive suppression of inter-user interference and inter-stream interference,realizing the improvement of system capacity.Specifically,the full rank constraint of the desired signal,the low power constraint of the inter-stream interference signal,and the low rank constraint of the interuser interference signal are constructed.At the same time,with the help of the Min-Max method,the interference suffered by each user is suppressed separately.Simulation results show that the proposed algorithm can achieve higher system capacity and relatively better outage probability performance.4)For the scenario of relay-assisted MIMO interference channel networks,by adopting the additional transmission links provided by the relay,a relay-assisted maximizing the signal-to-interference-plus-noise ratio mechanism is proposed,and the optimization algorithm based on maximizing the signal-to-interference-plus-noise ratio in relayassisted MIMO interference channel networks is designed.The optimization algorithm can deal with the problem of transmission link limitation in the traditional MIMO interference channel networks,and further improve the system capacity.Specifically,using the properties of channel reciprocity and generalized Rayleigh quotient,and with the help of the system model of the forward transmission link and the backward transmission link,the receive filtering matrix of relay,the transmit precoding matrix of relay,the relay processing matrix,the receive filtering matrix of receiver and the transmit precoding matrix of transmitter are designed to maximize the signal-to-interference-plus-noise ratio.Simulation results show that the proposed algorithm can significantly improve the system capacity performance with the help of the additional transmission links provided by the relay.In summary,in order to deal with the coexistence of inter-user interference and interstream interference in multi-user MIMO networks,the differences in user communication capabilities and the dynamics of communication requirements,this thesis focuses on the analysis and research of joint optimization of received signal power and space dimensions,the joint optimization of transceiver and power based on user priority,the transceiver optimization based on rank constraint at stream level,and the optimization based on the relay-assisted maximizing the signal-to-interference-plus-noise ratio.Based on the above research,we have effectively suppressed the interference signal,and designed the automatic adjustment mechanism of the algorithms,which significantly improve the system capacity of the multi-user MIMO networks.