Abstract
Channel estimation is crucial in millimeter wave (mmWave) communication systems. The conflict between high angular resolution and heavy training overhead is a bottleneck to apply beam training-based channel estimation schemes such as hierarchical search and compressed sensing. In this paper, a novel two-stage adaptive high-resolution channel estimation (AHRCE) approach is proposed for mmWave system. In the first stage, hierarchical search based on normal-resolution codebooks is exploited to acquire the coarse estimated multipath components (MPCs). The number of measurements can be dynamically adjusted among training levels. In the second stage, a sparse signal recovery method to achieve high-resolution angles of departure (AoDs) and angles of arrival (AoAs) is introduced. The accurately estimated channel is estimated without quantization error by calculating a set of ratio metrics. Numerical results show that our proposed scheme achieves a more efficient tradeoff between the training overhead and mean square error (MSE) performance in broader SNR region than the other existing method.
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Acknowledgement
This work was supported by the Beijing Natural Science Foundation under Grant L192032, the Chinese Government Scholarship under Grant 201906475006, the National Key R&D Program of China under Grant 2019YFB1406500, and the Shandong Province Key R&D Program Major Scientific Innovation Project under Grant 2019JZZY020901.
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Zhao, Y., Guo, L., Dong, C., Mu, X. (2020). Adaptive High-Resolution Channel Estimation Approach for Millimeter Wave MIMO Systems. In: Wang, Y., Fu, M., Xu, L., Zou, J. (eds) Signal and Information Processing, Networking and Computers. Lecture Notes in Electrical Engineering, vol 628. Springer, Singapore. https://doi.org/10.1007/978-981-15-4163-6_15
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DOI: https://doi.org/10.1007/978-981-15-4163-6_15
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