Abstract
In order to reduce the hardware complexity and cost of mmWave transceivers, hybrid beamforming techniques have been developed, which rely on the channel state information (CSI) available to the receiver and/or transmitter. In mmWave channel estimation, the compressed sensing (CS)-based algorithms like orthogonal matching pursuit (OMP) have been widely studied to take the advantages of the sparse characteristics of mmWave channels. Specifically, the OMP-assisted adaptive codebook channel estimation has the merit of reduced implementation complexity, but it performs undesirably in low signal to noise ratio (SNR) scenarios. To circumvent this problem, in this paper, we develop an improved adaptive codebook channel estimation algorithm for orthogonal frequency division multiplexing (OFDM) mmWave systems, which enhances the estimation performance by exploiting the multi-carrier signals for joint decision making. Our studies show that the proposed channel estimation is capable of significantly improving the estimation accuracy at low SNR, while enjoying a low complexity for implementation.
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