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Chapter

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Title

Radio Environment Map and Deep Q-Learning for 5G Dynamic Point Blanking

Authors

[ 1 ] Instytut Radiokomunikacji, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ SzD ] doctoral school student | [ P ] employee

Scientific discipline (Law 2.0)

[2.3] Information and communication technology

Year of publication

2022

Chapter type

chapter in monograph / paper

Publication language

english

Keywords
EN
  • 5G
  • Massive MIMO
  • Radio Environment Map
  • Dynamic Point Blanking
  • Deep Q-Learning
Abstract

EN Dynamic Point Blanking (DPB) is one of the Coordinated MultiPoint (CoMP) techniques, where some Base Stations (BSs) can be temporarily muted, e.g., to improve the cell-edge users throughput. In this paper, it is proposed to obtain the muting pattern that improves cell-edge users throughput with the use of a Deep Q-Learning. The Deep Q-Learning agent is trained on location-dependent data. Simulation studies have shown that the proposed solution improves cell-edge user throughput by about 20.6%.

Pages (from - to)

1 - 3

DOI

10.23919/SoftCOM55329.2022.9911517

URL

https://ieeexplore.ieee.org/document/9911517

Book

2022 30th International Conference on Software, Telecommunications and Computer Networks, SoftCOM 2022, Split, Croatia, September 22 - 24, 2022

Presented on

30th International Conference on Software, Telecommunications and Computer Networks, SoftCOM 2022, 22-24.09.2022, Split, Croatia

Ministry points / chapter

20

Ministry points / conference (CORE)

70

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