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Efficient Beam Training and Sparse Channel Estimation for Millimeter Wave Communications Under Mobility.

, , , and . IEEE Trans. Commun., 68 (10): 6583-6596 (2020)

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Greedy Data-Aided Active User Detection for Massive Machine Type Communications., , and . IEEE Wirel. Commun. Lett., 8 (4): 1224-1227 (2019)New Beam Tracking Technique for Millimeter Wave-band Communications., , , and . CoRR, (2017)Efficient Beam Training and Sparse Channel Estimation for Millimeter Wave Communications Under Mobility., , , and . IEEE Trans. Commun., 68 (10): 6583-6596 (2020)Near-ultrasound communication for TV's 2nd screen services., , , , , , , and . MobiCom, page 42-54. ACM, (2016)Sampling-based tracking of time-varying channels for millimeter wave-band communications., , , , , and . ICC, page 1-6. IEEE, (2017)Estimation of Dynamically Varying Support of Sparse Signals via Sequential Monte-Carlo Method., , , and . IEEE Trans. Signal Process., (2020)Greedy Recovery of Sparse Signals with Dynamically Varying Support., , , and . EUSIPCO, page 578-582. IEEE, (2018)Efficient Beam Training and Channel Estimation for Millimeter Wave Communications Under Mobility., , , , and . CoRR, (2018)Dedicated Beam-based Channel Training Technique for Millimeter Wave Communications with high Mobility., , , , and . EUSIPCO, page 1830-1834. IEEE, (2018)Greedy Sparse Channel Estimation for Millimeter Wave Communications., , and . TENCON, page 1628-1632. IEEE, (2018)