Q-learning based cell selection for UE outage reduction in heterogeneous networks

Toshihito Kudo, Tomoaki Ohtsuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Cell range expansion (CRE) is a load balancing technique that virtually expands a pico cell range by adding a bias value to the pico received power, instead of increasing transmit power of the pico base station (PBS); It can make cell-edge throughput and overall network throughput improved. CRE disperses the load of macro base stations (MBSs) on PBSs, so that it can reduce the number of UE outages. Although the configuration of the bias values of each user equipment (UE) has potential to reduce UE outages compared with the common bias value configuration among UEs, the common one is applied in the majority of related works for simplicity. In this article, we propose a scheme to select a cell by using Q-learning algorithm where each UE learns to which cell to send a service request to reduce the number of UE outages from its past experience independently. Simulation results show that the proposed scheme has the minimum number of UE outages in the system. Moreover, they show that it reduces the number of UE outages and the required memory size, compared with our previous proposed method.

Original languageEnglish
Title of host publicationIEEE Vehicular Technology Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781479944491, 9781479944491
DOIs
Publication statusPublished - 2014 Nov 24
Event80th IEEE Vehicular Technology Conference, VTC 2014-Fall - Vancouver, Canada
Duration: 2014 Sep 142014 Sep 17

Other

Other80th IEEE Vehicular Technology Conference, VTC 2014-Fall
CountryCanada
CityVancouver
Period14/9/1414/9/17

Fingerprint

Q-learning
Heterogeneous networks
Heterogeneous Networks
Outages
Cell
Base stations
Throughput
Range of data
Configuration
Load Balancing
Learning algorithms
Expand
Resource allocation
Macros
Learning Algorithm
Simplicity
Data storage equipment

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Applied Mathematics

Cite this

Kudo, T., & Ohtsuki, T. (2014). Q-learning based cell selection for UE outage reduction in heterogeneous networks. In IEEE Vehicular Technology Conference [6966140] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VTCFall.2014.6966140

Q-learning based cell selection for UE outage reduction in heterogeneous networks. / Kudo, Toshihito; Ohtsuki, Tomoaki.

IEEE Vehicular Technology Conference. Institute of Electrical and Electronics Engineers Inc., 2014. 6966140.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kudo, T & Ohtsuki, T 2014, Q-learning based cell selection for UE outage reduction in heterogeneous networks. in IEEE Vehicular Technology Conference., 6966140, Institute of Electrical and Electronics Engineers Inc., 80th IEEE Vehicular Technology Conference, VTC 2014-Fall, Vancouver, Canada, 14/9/14. https://doi.org/10.1109/VTCFall.2014.6966140
Kudo T, Ohtsuki T. Q-learning based cell selection for UE outage reduction in heterogeneous networks. In IEEE Vehicular Technology Conference. Institute of Electrical and Electronics Engineers Inc. 2014. 6966140 https://doi.org/10.1109/VTCFall.2014.6966140
Kudo, Toshihito ; Ohtsuki, Tomoaki. / Q-learning based cell selection for UE outage reduction in heterogeneous networks. IEEE Vehicular Technology Conference. Institute of Electrical and Electronics Engineers Inc., 2014.
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