基于IMMKF算法的5G无线通信毫米波数据混合波束跟踪OA

The mixed beam channel of 5G wireless communication millimeter wave data has sparse multipath and dynamic time-varying characteristics,which leads to insufficient tracking accuracy.Therefore,an interactive multi model Kalman filter(IMMKF)algo-rithm based tracking method for 5G wireless communication millimeter wave data mixed beam is proposed.Construct a millimeter wave channel model,use ray tracing model to characterize the sparse multipath characteristics of the channel,use first-order Gaussian Markov process to describe the dynamic time-varying characteristics of the channel,and combine digital/analog hybrid beamforming system trans-mission model to analyze the signal processing architecture of the transmitting and receiving ends.Using the IMMKF algorithm,the signal emission angle(AoD),arrival angle(AoA),and channel gain are used as mixed beam tracking state variables to achieve real-time state es-timation.Using model probability update to select the optimal model,and by outputting the weighted and merged results of multiple mod-el interactions,the state variable tracking of mixed wave velocity is achieved.The experimental results show that the proposed method has excellent tracking accuracy,anti-interference ability,and robustness in different scenarios,which can reduce the fluctuation amplitude of 5G wireless communication in different scenarios and maintain the stability of the communication link.