Transmission Strategies for Throughput Maximization in High-Speed-Train Communications: From Theoretical Study to Practical Algorithms

This paper focuses on improving the downlink throughput of the base station (BS)-to-train communication link in a high-speed train (HST) scenario. First, we provide a theoretical study of the throughput maximization problem in a single-cell multiple-input-multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) train scenario with and without cooperation among carriages. The aim is to give fundamental insight into the problem rather than providing practically realizable algorithms. The theoretical study suggests that it is highly advantageous to exploit the size of the train by increasing the number of antennas and further allowing the carriages to cooperate. In the practical system-level study, we propose two low-complexity MIMO-OFDM transmission schemes, which are based on simple antenna selection (AS) methods with spatial multiplexing. The main idea is to select the best transmit antennas among different antenna combinations by comparing their estimated throughput performances. The simulation results show that the proposed algorithms outperform Long-Term Evolution (LTE)-based dynamic rank transmission schemes in terms of throughput and computational load in practical HST scenarios. Unlike the exhaustive search type of dynamic transmission schemes, our simple algorithms are also applicable to large antenna arrays. In conclusion, large antenna arrays with simple AS and spatial multiplexing transmission strategies seem to be potential solutions to the significant improvement of the throughput of the BS-to-train link in HST scenarios.