Ergodic capacity analysis of remote radio head associations in cloud radio access networks

Mugen Peng, Shi Yan, H. Vincent Poor

Research output: Contribution to journalArticlepeer-review

118 Scopus citations


Characterizing user to remote radio head (RRH) association strategies in cloud radio access networks (C-RANs) is critical for performance optimization. In this letter, the single nearest and $N$-nearest RRH association strategies are presented, and the corresponding impact on the ergodic capacity of C-RANs is analyzed, where RRHs are distributed according to a stationary point process. Closed-form expressions for the ergodic capacity of the proposed RRH association strategies are derived. Simulation results demonstrate that the derived uplink closed-form capacity expressions are accurate. Furthermore, the analysis and simulation results show that the ergodic capacity gain is not linear with either the RRH density or the number of antennas per RRH. The ergodic capacity gain from the RRH density is larger than that from the number of antennas per RRH, which indicates that the association number of the RRH should not be bigger than 4 to balance the performance gain and the implementation cost.

Original languageEnglish (US)
Article number6798725
Pages (from-to)365-368
Number of pages4
JournalIEEE Wireless Communications Letters
Issue number4
StatePublished - Aug 2014

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering


  • Cloud radio access networks (C-RANs)
  • cell association,performance analysis
  • large-scale cooperation


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