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SCIENCE CHINA Information Sciences, Volume 60, Issue 8: 080305(2017) https://doi.org/10.1007/s11432-017-9139-4

A novel 3D frequency domain SAGE algorithm with applications to parameter estimation in mmWave massive MIMO indoor channels

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  • ReceivedMay 9, 2017
  • AcceptedJun 13, 2017
  • PublishedJul 5, 2017

Abstract

Millimeter wave (mmWave) and massive multiple-input multiple-output (MIMO) wireless communication channels show some new characteristics different from conventional channels. In order to have an in-depth understanding of mmWave massive MIMO channels, we conduct channel measurements at 16, 28, and 38 GHz frequency bands using virtual large horizontal planar arrays in an indoor office environment. First, a three dimensional (3D) frequency domain (FD) parameter estimation algorithm extended from the space alternating generalized expectation-maximization (SAGE) algorithm is proposed and used to process the measurement data. Second, by dividing the large array into several sub-arrays and calculating power delay profiles (PDPs), power azimuth angle profiles (PAAPs), and power elevation angle profiles (PEAPs), we analyze the changes of delay, azimuth angle of arrival (AAoA), and elevation AoA (EAoA) over the large array. We find that the spatial cross-correlation functions (SCCFs) calculated along different directions of the planar array exhibit significant variations. Third, the comparison of the averaged PDPs (APDPs) at three different frequency bands shows that the attenuation increases when mmWave channels move to high frequency bands. Furthermore, SCCFs of channels at three frequency bands are also compared for two uniform linear arrays (ULAs). We draw conclusion that the correlation coefficients can be affected by not only measurement environments, but also the relative angle between transmitter (Tx) pointing direction and receiver (Rx) large array, and the operating frequency bands.


Acknowledgment

This work was supported by EU H2020 ITN 5G Wireless Project (Grant No. 641985), EU H2020 RISE TESTBED Project (Grant No. 734325), EU FP7 QUICK Project (Grant No. PIRSES-GA-2013-612652), EPSRC TOUCAN project (Grant No. EP/L020009/1), National Natural Science Foundation of China (Grant Nos. 61210002, 61371110), Xinwei Telecom Technology Inc. (Grant No. 11131701), and Fundamental Research Funds of Shandong University (Grant No. 2017JC009).

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