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Channel estimation (CE) for millimeter-wave (mmWave) lens-array suffers fromprohibitive training overhead, whereas the state-of-the-art solutions requirean extra complicated radio frequency phase shift network. By contrast,lens-array using antenna switching network (ASN) simplifies the hardware, butthe associated CE is a challenging task due to the constraint imposed by ASN.This paper proposes a compressive sensing (CS)-based CE solution forfull-dimensional (FD) lens-array, where the mmWave channel sparsity isexploited. Specifically, we first propose an approach of pilot training underthe more severe haraware constraint imposed by ASN, and formulate theassociated CE of lens-array as a CS problem. Then, a redundant dictionary istailored for FD lens-array to combat the power leakage caused by the continuousangles of multipath components. Further, we design the baseband pilot signalsto minimize the total mutual coherence of the measurement matrix based on CStheory for more reliable CE performance. Our solution provides a framework forapplying CS techniques to lens-array using simple and practical ASN. Simulationresults demonstrate the effectiveness of the proposed scheme.

Compressive Sensing Based Channel Estimation for Millimeter-Wave Full-Dimensional MIMO with Lens-Array