Performance Analysis of XL-MIMO-OFDM Systems for High-Speed Train Communications

Extremely large-scale multiple-input multiple-output (XL-MIMO) has been deemed a breakthrough technology that holds significant potential for next-generation communication. Applying XL-MIMO to high-speed train (HST) communications improves network capacity and transmission quality, overcoming the limitations of traditional technology. In this paper, we analyze the performance of XL-MIMO systems using extremely large aperture arrays (ELAAs) in line-of-sight (LoS) scenarios and investigate the factors that affect spectral efficiency (SE), including deployment modes, number of train antennas (TAs) or access points (APs), antenna area, HST position, and combining methods. We find that the minimum mean square error (MMSE) combining and large-scale fading decoding (LSFD) cooperation are crucial for HST communications. Moreover, numerical results show that increasing the number of APs enhances the average SE and decreases the distance between the APs and the rail track, leading to optimal performance. Additionally, reducing the number of TAs and antenna area can also minimize the impact of Doppler frequency offset (DFO). Furthermore, if the total number of antennas is kept constant, further improving the average SE can be achieved by decreasing the number of antennas per AP and increasing the number of APs.