1st International ICST Conference on Bio Inspired Models of Network, Information and Computing Systems

Research Article

An ecology-based adaptive network control scheme for radio resource management in heterogeneous wireless networks

  • @INPROCEEDINGS{10.1145/1315843.1315885,
        author={Jie Chen and Kai Yu and Guang Yang and ZhiYong  Feng and Yang   Ji and Ping  Zhang and Qing  Huang and Yong  Bai and Lan  Chen and Masahiro Minomo},
        title={An ecology-based adaptive network control scheme for radio resource management in heterogeneous wireless networks},
        proceedings={1st International ICST Conference on Bio Inspired Models of Network, Information and Computing Systems},
        publisher={ACM},
        proceedings_a={BIONETICS},
        year={2006},
        month={12},
        keywords={Heterogeneous wireless networks L-V model Mapping relationship Net revenue Radio Resource Management.},
        doi={10.1145/1315843.1315885}
    }
    
  • Jie Chen
    Kai Yu
    Guang Yang
    ZhiYong Feng
    Yang Ji
    Ping Zhang
    Qing Huang
    Yong Bai
    Lan Chen
    Masahiro Minomo
    Year: 2006
    An ecology-based adaptive network control scheme for radio resource management in heterogeneous wireless networks
    BIONETICS
    ACM
    DOI: 10.1145/1315843.1315885
Jie Chen1, Kai Yu1, Guang Yang1, ZhiYong Feng1, Yang Ji1, Ping Zhang1, Qing Huang2, Yong Bai2, Lan Chen2, Masahiro Minomo2
  • 1: Beijing Univ. Posts and Telecommunications (BUPT), China
  • 2: NTT-DoCoMo Beijing Communication Labs, China

Abstract

The major challenge in future heterogeneous wireless networks is to promote the network welfare by well designing the radio resource management (RRM). Due to the similarity of both the ecological system and the heterogeneous wireless networks on the competitiveness, we propose a novel ecology-based adaptive network control (EBANC) scheme for RRM to optimize the network revenue, which introduces the Lotka-Volterra competition equations (L-V model) to predict the outcome of competitiveness. The proposed EBANC consists of two key algorithms, which are access selection algorithm on the user side and the price control algorithm on the network side. The simulation results exhibit the better performance of the EBANC scheme compared with other existing access selection scheme.