Abstract
This paper addresses the problem of downlink channel estimation in millimeter wave (mmWave) massive multiple input multiple output (MIMO)-orthogonal frequency division multiplexing (OFDM) systems, where wideband frequency selective fading channels are considered. By exploiting the sparse scattering nature of mmWave channel, we consider channel estimation as three dimensional (3D) (including angles of departure/arrival and the time delay) line spectrum estimation. To achieve super-resolution channel estimation, we propose a decomposable 3D atomic norm minimization estimation method. This method decomposes the 3D estimation problem into two separate dimensions to reduce the computational complexity, where time delays are estimated only in the OFDM system. Simulation results show that the proposed method can achieve comparable mean square errors as the conventional vectorized ANM at much lower computational complexity.
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Notes
- 1.
Since the number of subcarriers used for training is proportional to the computational complexity of channel estimation, the complexity can be mitigated with as few subcarriers as possible.
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Acknowledgments
This work was supported by the National Natural Science Foundation of China (Grant No. 61871023 and 61572070) and the Fundamental Research Funds for the Central Universities (Grant No. 2017YJS035 and 2016JBZ003).
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An, Q., Jing, T., Wen, Y., Duan, Z., Huo, Y. (2019). Decomposable Atomic Norm Minimization Channel Estimation for Millimeter Wave MIMO-OFDM Systems. In: Biagioni, E., Zheng, Y., Cheng, S. (eds) Wireless Algorithms, Systems, and Applications. WASA 2019. Lecture Notes in Computer Science(), vol 11604. Springer, Cham. https://doi.org/10.1007/978-3-030-23597-0_1
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DOI: https://doi.org/10.1007/978-3-030-23597-0_1
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