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DATA-AIDED FAST BEAMFORMING SELECTION FOR 5G

Citation Author(s):
Gabriel Falcao, Leonel Sousa
Submitted by:
Joao Gante
Last updated:
13 April 2018 - 5:25am
Document Type:
Poster
Document Year:
2018
Event:
Presenters Name:
Leonel Sousa
Paper Code:
4506

Abstract 

Abstract: 

Millimeter wave frequencies paired up with MIMO antennas
employing beamforming are seen as critical enablers of next gen-
eration networks. However, selecting the most beneficial beamform-
ing weights in a codebook-enabled downlink transmitter is a lengthy
task, as the existing methods rely on some form of channel mea-
surement. In fact, if the used codebook is too large, the traditional
methods might fail to select an appropriate entry within the channel
coherence time.
In this paper, a new method to assist the beam selection is pro-
posed, based on data obtained from previous connections. Through
the continuous update of the set of optimal codebook entries for
each position, the search space required for each connection can be
greatly reduced if the user position is known. The simulations per-
formed show that retrieving the sets of codebook entries in single
user scenarios required less than 51 ns. For multi-user scenarios, re-
sults exceeding 10 simultaneous users using a 16 entry codebook
were achieved, requiring less than 600 µs. The obtained results
show that the proposed method can greatly reduce the beam selec-
tion latency and energy requirements, opening the door to powerful
millimeter wave networks.

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