Channel-aware resource allocation for energy-efficient cloud radio access networks under outage specifications

Pei Rong Li, Kai-Ten Feng*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


This paper investigates a cloud radio access network (C-RAN) architecture for future wireless network, which focuses on centralized processing for spatially distributed remote radio heads (RRHs). Our main goal is to promote an energy efficient C-RAN under the consideration of multiple access interference (MAI) and imperfect channel state information at the transmitter (CSIT) via outage-aware resource allocation. The closed-form expression of fading-induced outage probability for each transceiver pair will be established by analyzing the statistical property of signal-to-interference-plus-noise. In the course of finding feasible solutions to enhance energy efficiency, the optimization procedures named C-RAN-based energy efficient power allocation (CEEPA) and low-complexity CEEPA are proposed. As the number of RRHs grows to infinity, the deterministic equivalents of performance metrics can be derived by applying recent results from random matrix theorem, which lead to an efficient way to obtain the asymptotic-optimal resource allocation policy. Also, the regularized zero-forcing precoding technique is adopted to mitigate MAI and can tackle the impact of imperfect CSIT thanks to the derivation of deterministic equivalents. Numerical simulations show that the proposed resource allocation schemes can provide better energy efficiency and the accuracy of asymptotic expressions is also verified. Furthermore, the merit of a distributed antenna system is demonstrated through the comparison with centralized antenna system.

Original languageEnglish
Article number8026557
Pages (from-to)7389-7403
Number of pages15
JournalIEEE Transactions on Wireless Communications
Issue number11
StatePublished - 1 Nov 2017


  • Asymptotic analysis
  • Cloud radio access network (C-RAN)
  • Energy efficiency
  • Outage probability

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