Abstract
In Japan, high-speed ground transportation service using linear motors at speeds of 500 km/h is scheduled to begin in 2027. To accommodate 5G services in trains, a subcarrier spacing frequency of 30 kHz will be used instead of the typical 15 kHz subcarrier spacing to mitigate Doppler effects in such high-speed transport. Furthermore, to increase the cell size of the 5G mobile system, multiple base station antennas will transmit identical downlink (DL) signals to form an expanded cell size along the train rails. In this situation, the forward and backward antenna signals are Doppler-shifted in opposite directions, respectively, so the receiver in the train may suffer from estimating the exact Channel Transfer Function (CTF) for demodulation. In a previously published paper, we proposed a channel estimator based on Delay and Doppler Profiler (DDP) in a 5G SISO (Single Input Single Output) environment and successfully implemented it in a signal processing simulation system. In this paper, we extend it to 2×2 MIMO (Multiple Input Multiple Output) with spatial multiplexing environment and confirm that the delay and DDP based channel estimator is also effective in 2×2 MIMO environment. Its simulation performance is compared with that of a conventional time-domain linear interpolation estimator. The simulation results show that in a 2×2 MIMO environment, the conventional channel estimator can barely achieve QPSK modulation at speeds below 100 km/h and has poor CNR performance versus SISO. The performance degradation of CNR against DDP SISO is only 6dB to 7dB. And even under severe channel conditions such as 500km/h and 8-path inverse Doppler shift environment, the error rate can be reduced by combining the error with LDPC to reduce the error rate and improve the performance in 2×2 MIMO. QPSK modulation scheme in 2×2 MIMO can be used under severe channel conditions such as 500 km/h and 8-path inverse Doppler shift environment.