Abstract
In millimeter wave (mmWave) communication systems, large antenna arrays are used to compensate high path loss. While the large array provides high beamforming gain, it also poses a challenge in channel estimation. Since mmWave channels are likely to be sparse in angular domain, the channel estimation can be converted into a sparse recovery problem, and compressed sensing (CS) can be leveraged for the channel estimation. However, conventional non-adaptive CS algorithms show poor recovery performance with low signal-to-noise ratio (SNR), which is common before beamforming in mmWave channels. Although recently developed adaptive CS schemes perform better in a low SNR regime, their excessive feedback requirement hinders practical usage. In this paper, we propose a two-stage CS scheme that requires one-time feedback and is robust to noise, which can be regarded as a compromise between the two approaches. Sufficient conditions for the support recovery with the proposed scheme are characterized, and its effectiveness is also shown numerically.
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