Technical Report, Feb. 1, 2019
Machine Learning in Downlink Coordinated Multipoint in Heterogeneous Networks
Faris B. Mismar and
Brian L. Evans
Department of Electrical and Computer Engineering,
Wireless Networking and Communications Group,
The University of Texas at Austin,
Austin, TX 78712 USA
faris.mismar@utexas.edu -
bevans@ece.utexas.edu
Paper
Multiantenna Communications Project
Abstract
We propose a method for downlink coordinated multipoint (DL CoMP) in
heterogeneous fifth generation New Radio (NR) networks.
The primary contribution of our paper is to apply online machine learning
using a support vector machine (SVM) classifier in the physical layer to
enhance the user throughput in a scalable network environment.
Our simulation results show improvement in both the macro and pico base
station peak throughputs due to the informed triggering of the multiple
DL CoMP radio streams as learned by the SVM classifier.
COPYRIGHT NOTICE: All the documents on this server
have been submitted by their authors to scholarly journals or conferences
as indicated, for the purpose of non-commercial dissemination of
scientific work.
The manuscripts are put on-line to facilitate this purpose.
These manuscripts are copyrighted by the authors or the journals in which
they were published.
You may copy a manuscript for scholarly, non-commercial purposes, such
as research or instruction, provided that you agree to respect these
copyrights.
Last Updated 02/02/19.