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Sensors 2017, 17(9), 2009; doi:10.3390/s17092009

Position Fingerprint-Based Beam Selection in Millimeter Wave Heterogeneous Networks

School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
Author to whom correspondence should be addressed.
Received: 14 July 2017 / Revised: 28 August 2017 / Accepted: 30 August 2017 / Published: 1 September 2017
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The traditional beam selection algorithms determine the optimal beam direction by feeding back the perfect channel state information (CSI) in a millimeter wave (mmWave) massive Multiple-Input Multiple-Output (MIMO) system. Popular beam selection algorithms mostly focus on the methods of feedback and exhaustive search. In order to reduce the extra computational complexity coming from the redundant feedback and exhaustive search, a position fingerprint (PFP)-based mmWave multi-cell beam selection scheme is proposed in this paper. In the proposed scheme, the best beam identity (ID) and the strongest interference beam IDs from adjacent cells of each fingerprint spot are stored in a fingerprint database (FPDB), then the optimal beam and the strongest interference beams can be determined by matching the current PFP of the user equipment (UE) with the PFP in the FPDB instead of exhaustive search, and the orthogonal codes are also allocated to the optimal beam and the strongest interference beams. Simulation results show that the proposed PFP-based beam selection scheme can reduce the computational complexity and inter-cell interference and produce less feedback, and the system sum-rate for the mmWave heterogeneous networks is also improved. View Full-Text
Keywords: millimeter wave; multi-cell; heterogeneous networks; position fingerprint matching; beam selection millimeter wave; multi-cell; heterogeneous networks; position fingerprint matching; beam selection

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Zhang, Z.; Chen, Y. Position Fingerprint-Based Beam Selection in Millimeter Wave Heterogeneous Networks. Sensors 2017, 17, 2009.

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