Performance analysis of multi-user diversity in heterogeneous cooperative communication systems

  • Authors:
  • Mugen Peng;Wenbo Wang;Jie Zhang

  • Affiliations:
  • Key Laboratory of Universal Wireless Communications in Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China 100876;Key Laboratory of Universal Wireless Communications in Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China 100876;Department of Computing and Information Systems, University of Bedfordshire, Luton, UK LU1 3JU

  • Venue:
  • Wireless Networks
  • Year:
  • 2010

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Abstract

The heterogeneous cooperative relaying technique can be utilized to complete the hierarchical convergence for the multi-radio access networks, where the single heterogeneous cooperative relay is selected and the maximal-ratio combining (MRC) scheme is utilized to achieve the cooperative diversity gain. In order to evaluate performances of the hierarchical convergence mechanism, this paper theoretically investigates the key factors of the multi-user diversity (MUD) gain, the heterogeneous cooperative diversity gain and the large scale fading of the first and second links. The tight closed-form expressions in terms of the outage probability and the average symbol error rate are derived for evaluating how and with what factors impact on the system performance. The analytical and simulation results show that the number of heterogeneous cooperative relay nodes (HCRNs)M and the number of destination stations (DSs)K have great impacts on performances, and the order of outage probability is (M + 1)K. The large scale fading ratio of the first hop to the second hop also has a big impact on performances. Thus in the real network, we can utilize advanced radio resource management schemes to achieve a high multi-user diversity, instead of configuring too many HCRNs for the heterogeneous cooperative diversity gain. Furthermore, we can guarantee the transmission quality between the BS and HCRNs via the network planning to optimize the overall network performance.