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Signal-to-noise ratio(SNR) and channel estimations are critical for 60-GHz communications to track the optimal transmission and reception beam pairs.However,the excessive pilot overhead for the estimations severely reduces system throughput in fast-rotation scenarios.In order to address this problem,we firstly demonstrate the potential sparseness property of 60-GHz channel in beam tracking;subsequently,via exploiting this property,we propose a novel compressed SNR-and-channel estimation.The estimation is conducted in a three-stage fashion,including the unstructured estimation,nonzero-tap detection,and structured estimation with nonzero-tap location.Numerical simulations show that,in the case of substantial reduction of the pilot overhead,the proposed estimator still reveals a significant improvement in terms of estimation performance over the scheme in IEEE 802.11 ad.Furthermore,it is also demonstrated that the proposed SNR and channel estimators can approach the lower bounds in sparse channels so long as SNR exceeds 8 dB.
Signal-to-noise ratio (SNR) and channel estimations are critical for 60-GHz communications to track the optimal transmission and reception beam pairs. Despite excessive loss of system throughput in fast-rotation applications. to address this problem, we initially demonstrate the potential sparseness property of 60-GHz channel in beam tracking; subsequently, via exploiting this property, we propose a novel compressed SNR-and-channel estimation. The estimation is conducted in a three-stage fashion , including the unstructured estimation, nonzero-tap detection, and structured estimation with nonzero-tap location. Numerical simulations show that in the case of substantial reduction of the pilot overhead, the proposed estimator still reveals a significant improvement in terms of estimation performance over the scheme in IEEE 802.11 ad. Future and it is also demonstrated that the proposed SNR and channel estimators can approach the lower bounds in sparse channels so long as SNR exceeds 8 dB.