Hybrid millimetre‐wave channel simulation approach based on long short‐term memory networks

Abstract

In order to overcome the disadvantages of traditional channel simulation approaches and achieve more accurate millimetre-wave (mmWave) channel simulation under the condition of limited measured data, a novel Long Short-term Memory Networks (LSTM) based hybrid mmWave channel simulation approach is proposed in this work. The proposed hybrid approach takes advantages of LSTM-based time-varying model of path loss and large-scale channel parameters, statistical model of intra-cluster multipath parameters and ray tracing, which are able to accurately simulate path loss, large-scale channel parameters, multipath parameters and channel impulse responses, respectively. Based on the mmWave channel data measured in the waiting hall of Qingdaobei Railway Station, it is verified that the simulation results of our proposed hybrid approach are in good agreement with the measured data and better than that of existing channel simulation approaches. The hybrid channel simulation approach proposed in this work has important application value for channel modelling and simulation in the case of small amount of data.