Multi-Agent RL based User-Centric Spectrum Allocation Scheme in D2D Enabled Hetnets

Kamran Zia, Nauman Javed, M Nadeem Sial, Sohail Ahmed, Farrukh Pervez

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

7 Citations (Scopus)

Abstract

Device to device (D2D) communication technology is widely considered in 5G for providing higher data rates and increase network capacity. The performance benefits of D2D communication are best achieved if it takes place in shared mode in which it reuses the spectrum being utilized by conventional cellular users. This induces significant challenges in allocating resources because of severe interference among D2D and cellular users. Moreover, centralized resource allocation techniques proposed in literature for D2D users can no longer be practical in dense heterogeneous networks considered for 5G. In this paper, we present a distributed learning based spectrum allocation scheme in which D2D users learn the environment and autonomously select spectrum resources to maximize their Throughput and Spectral Efficiency (SE) while causing minimum interference to the cellular users. We have employed distributed learning in a stochastic geometry based realistic network. Our evaluation results show that the employed learning scheme enables users to achieve high Throughput and Spectral Efficiency while meeting QoS requirements of macro and femto tier.
Original languageEnglish
Title of host publication2018 IEEE 23rd International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)
DOIs
Publication statusPublished - Sept 2018
Externally publishedYes
Event23rd International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2018 - Barcelona, Spain
Duration: 17 Sept 201819 Sept 2018
Conference number: 23

Conference

Conference23rd International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2018
Abbreviated titleCAMAD 2018
Country/TerritorySpain
CityBarcelona
Period17/09/1819/09/18

Keywords

  • n/a OA procedure

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