An adaptive channel estimation algorithm for millimeter wave cellular systems

The large bandwidth available with mmWave (millimeter Wave) makes it a promising candidate for 5th generation cellular networks. Proper channel estimation algorithms must be developed to enable beamforming in mmWave systems. In this paper, we propose an adaptive channel estimation algorithm that exploits the poor scattering nature of the mmWave channel and adjusts the training overhead adaptively with the change of channel quality for mmWave cellular systems. First, we use a short training sequence to estimate the channel parameters based on the two-dimensional discrete Fourier transform method. Then, we design a feedback scheme to adjust the length of the training sequence under the premise of ensuring the accuracy of the channel estimation. The key threshold in the feedback scheme is derived and its influence on the accuracy of the estimation results is analyzed. Simulation results confirm that the proposed algorithm can adjust the length of the training sequence adaptively according to the current channel condition maintaining a stable estimation accuracy.