Efficient Beamforming Training and Channel Estimation for mmWave MIMO-OFDM Systems

We consider the problem of channel estimation for millimeter wave
(mmWave) MIMO-OFDM systems. To efficiently probe the channel, the
transmitter forms multiple beams simultaneously and steer them
towards different directions. The objective of this paper is to
devise the beam-training patterns and develop an efficient
algorithm to estimate the channel. By exploiting the common
sparsity inherent in MIMO-OFDM mmWave channels, we develop a
sparse bipartite graph coding-based method for joint beamforming
training and channel estimation. Simulation results are provided
to show the effectiveness of the proposed method.