A Novel NE-DFT Channel Estimation Scheme for Millimeter-Wave Massive MIMO Vehicular Communications

Having the ability to provide an ultrafast and high-rate data exchange, millimeter-wave (mmWave) massive MIMO has been viewed as one of the technologies with the most potential for vehicular cellular systems in next-generation wireless communications. To alleviate the adverse influence of huge path losses, beamforming techniques are always introduced in various mmWave systems to provide sufficient channel gains. However, it is important to note that the traditional channel estimation algorithms may no longer be available in vehicular cellular networks due to the rapid movements of pedestrians and vehicles. Under this condition, this paper proposes a noise elimination-based discrete Fourier transform (DFT) channel estimation strategy, namely, the NE-DFT channel estimation strategy, for mmWave vehicular communications. Specifically, we first use the iterative cancellation method to initially estimate all path parameters. Then, to further improve the estimate accuracy, we set a decision threshold to determine the authenticity of the estimated paths. Furthermore, the energy distribution of each path in the channel is analyzed, and an additional estimation scheme is designed that enables a more accurate estimation of the previously estimated paths, which uses the comparison value between the total channel matrix energy and the actual signal matrix energy as an auxiliary judgment to successively select the path with the minimum comparison value until a sufficient number of real paths are selected. Finally, the channel matrix is reconstructed using the estimated channel parameters. Simulation results verify that the proposed NE-DFT channel estimation scheme can achieve much better NMSE performance than the conventional scheme, even in comparison with the time-variant channel.