Channel Estimation for Massive MIMO-OFDM Systems by Tracking the Joint Angle-Delay Subspace

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Abstract
In this paper, we propose joint angle-delay subspace based-channel estimation in single cell for broadband massive multiple-input and multiple-output systems employing orthogonal frequency division multiplexing modulation. Based on a parametric channel model, we present a new concept of the joint angle-delay subspace, which can be tracked by the low-complexity low-rank adaptive filtering algorithm. Then, we investigate an interference-free transmission condition that the joint angle-delay subspaces of the users reusing the same pilots are non-overlapping. Since the channel statistics are usually unknown, we develop a robust minimum mean square error (MMSE) estimator under the worst precondition of pilot decontamination, considering that the joint angle-delay subspaces of the interfering users fully overlap. Furthermore, motivated by the interference-free transmission criteria, we present a novel low-complexity greedy pilot scheduling algorithm to avoid the problem of initial value sensitivity. Simulation results show that the joint angle-delay subspace can be estimated effectively, and the proposed pilot reuse scheme combined with robust MMSE channel estimation offers significant performance gains.
Funding Information
  • Hong Kong Macao and Taiwan Science Technology Cooperation Program of China (2014DFT10290)
  • National High Technology Research and Development Program of China (2014AA01A704)
  • Natural Science Foundation of Jiangsu Province (BK20150630)
  • National Basic Research Program of China (2013CB336600)
  • National Natural Science Foundation of China (61271205, 61372100, 61501113, 61521061)

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