This is a code package is related to the following scientific article:

Jiakang Zheng, Jiayi Zhang, Emil Björnson, Zhetao Li and Bo Ai, "Cell-Free Massive MIMO-OFDM for High-Speed Train Communications," IEEE Journal on Selected Areas in Communications, to appear, 2022.

The package contains a simulation environment, based on Matlab, that reproduces some of the numerical results and figures in the article. We encourage you to also perform reproducible research!

Cell-free (CF) massive multiple-input multiple-output (MIMO) systems show great potentials in low-mobility scenarios, due to cell boundary disappearance and strong macro diversity. However, the great Doppler frequency offset (DFO) leads to serious inter-carrier interference in orthogonal frequency division multiplexing (OFDM) technology, which makes it difficult to provide high-quality transmissions for both high-speed train (HST) operation control systems and passengers. In this paper, we focus on the performance of CF massive MIMO-OFDM systems with both fully centralized and local minimum mean square error (MMSE) combining in HST communications. Considering the local maximum ratio (MR) combining, the large-scale fading decoding (LSFD) cooperation and the practical effect of DFO on system performance, exact closed-form expressions for uplink spectral efficiency (SE) expressions are derived. We observe that cooperative MMSE combining achieves better SE performance than uncooperative MR combining. In addition, HST communications with small cell and cellular massive MIMO-OFDM systems are compared in terms of SE. Numerical results reveal that the CF massive MIMO-OFDM system achieves a larger and more uniform SE than the other systems. Finally, the train antenna centric (TA-centric) CF massive MIMO-OFDM system is designed for practical implementation in HST communications, and three power control schemes are adopted to optimize the propagation of TAs for reducing the impact of the DFO.

The package includes ten simulation figures in the paper. The folder number corresponds to the number of the simulation figures in the paper.

This code package is licensed under the GPLv2 license. If you in any way use this code for research that results in publications, please cite our original article listed above.