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

Hanyu Wang, Jun Fang, Huiping Duan, Hongbin Li
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引用次数: 1

Abstract

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 beamtraining 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.
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毫米波MIMO-OFDM系统的有效波束形成训练和信道估计
研究了毫米波MIMO-OFDM系统的信道估计问题。为了有效地探测信道,发射机同时形成多个波束,并将它们引导到不同的方向。本文的目标是设计波束训练模式,并开发一种有效的信道估计算法。通过利用MIMO-OFDM毫米波信道固有的共同稀疏性,我们开发了一种基于稀疏二部图编码的联合波束形成训练和信道估计方法。仿真结果表明了该方法的有效性。
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