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Lecture/Seminar Graduate Student Seminar: Framework of Channel Estimation for Hybrid Analog-and-Digital Processing Enabled Massive MIMO Communications 2017-04-26 14:00:00

Speaker: Leyuan Pan
Supervisor: Dr. Xiaodai Dong


This seminar presents a general channel estimation problem in the massive multiple-input multiple-output (MIMO) system which employs the hybrid analog/digital precoding structure with limited radio-frequency (RF) chains. By properly designing RF combiners and performing multiple trainings, the proposed channel estimation can approach the performance of full-chain estimations depending on the degree of channel spatial correlation and the number of RF chains. Dealing with the hybrid channel estimation, the optimal combiner is theoretically derived by relaxing the constant-magnitude constraint in a specific single-training scenario, which is then extended to the design of combiners for multiple trainings by Sequential and Alternating methods. Further, we develop a technique to generate the phase-only RF combiners based on the corresponding unconstrained ones to satisfy the constant-magnitude constraints. The performance of the proposed hybrid channel estimation scheme is examined by simulations under both nonparametric and parametric channel models. The simulation results verify that the estimated CSI can approach the performance of full-chain estimations in terms of both mean square error (MSE) and achieved spectral efficiency. Moreover, a covariance matching method is proposed to obtain channel correlation in practice and the simulation verifies its effectiveness by evaluating the spectral efficiency performance in parametric channel models.

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Times 14:00:00 to 15:00:00
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