Journal of Convergence for Information Technology (융합정보논문지)

Convergence Society for SMB (중소기업융합학회)
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Hierarchical Dynamic Spectrum Management for Providing Network-wise Fairness in 5G Cloud RAN

5G Cloud RAN에서 네트워크 공평성 향상을 위한 계층적 적응 스펙트럼 관리 방법

  • Jo, Ohyun (Department of Computer Science, Chungbuk National University)
  • 조오현 (충북대학교 소프트웨어학과)
  • Received : 2020.04.19
  • Accepted : 2020.07.20
  • Published : 2020.07.28
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Abstract

A new resource management algorithm is proposed for 5G networks which have a coordinated network architecture. By sharing the contol information among multiple neighbor cells and managing in centralized structure, the propsed algorithm fully utilizes the benefits of network coordination to increase fairness and throughput at the same time. This optimization of network performance is achieved while operating within a tolerable amount of signaling overhead and computational complexity. Simulation results confirm that the proposed scheme improve the network capacity up to 40% for cell edge users and provide network-wise fairness as much as 23% in terms of the well-knwon Jain's Fainess Index.

본 논문에서는 셀 간 정보의 공유를 통한 협력이 가능한 연결된 네트워크 구조를 갖는 5G Cloud RAN 네트워크에 적용이 가능한 새로운 자원 관리 알고리즘을 제안한다. 제안 알고리즘은 네트워크 협력의 이점을 활용하여 공정성과 처리량을 동시에 증가시킨다. 이러한 네트워크 성능 최적화는 허용이 가능한 양의 신호 처리 오버헤드 및 계산 복잡도 내에서 달성될 수 있으며 시뮬레이션 결과는 셀 외곽 사용자에 대한 네트워크 용량이 기존의 방법 대비 40% 가량 향상되었으며 사용자간 공정성 또한 Jain의 공평성 지수를 기준으로 약 23% 향상되었음을 확인하였다.

Keywords

References

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