Adaptive cloud radio access networks: Compression and optimization

Thang X. Vu, Hieu Duy Nguyen, Tony Q.S. Quek, Sumei Sun

Research output: Contribution to journalArticlepeer-review

25 Citations (Scopus)


Future mobile networks are facing with exponential data growth due to the proliferation of diverse mobile equipment and data-hungry applications. Among promising technology candidates to overcome this problem, cloud radio access network (C-RAN) has received much attention. In this paper, we investigate the design of fronthaul in C-RAN uplink by focusing on the compression and optimization in fronthaul uplinks based on the statistics of wireless fading channels. First, we derive the system block error rate (BLER) under Rayleigh fading channels. In particular, upper and lower bounds of the BLER union bound are obtained in closed-form. From these bounds, we gain insight in terms of diversity order and limits of the BLER. Next, we propose adaptive compression schemes to minimize the fronthaul transmission rate subject to a BLER constraint. Furthermore, a fronthaul rate allocation is proposed to minimize the system BLER. It is shown that the uniform rate allocation approaches the optimal scheme as the total fronthauls' bandwidth increases. Finally, numerical results are presented to demonstrate the effectiveness of our proposed optimizations.

Original languageEnglish
Article number7590147
Pages (from-to)228-241
Number of pages14
JournalIEEE Transactions on Signal Processing
Issue number1
Publication statusPublished - 2017 Jan 1

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering


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