Multivariate fronthaul quantization for C-RAN downlink: Channel-adaptive joint quantization in the cloud

Wonju Lee, Osvaldo Simeone, Joonhyuk Kang, Shlomo Shamai Shitz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

In the downlink of the Cloud-Radio Access Network (C-RAN) cellular architecture, complex baseband signals are transmitted from a central unit (CU) in the cloud over digital fronthaul links to distributed radio units (RUs). The standard design of digital fronthauling is based on quantization that operates separately over each fronthaul link. In this paper, a fronthaul quantization scheme is proposed that, unlike conventional schemes, implements a joint quantization mapping across all fronthaul links that is adapted to the current channel conditions. As compared to the current standard approach, the proposed multivariate quantization (MQ) scheme only requires additional processing at the CU, while no modification is needed at the RUs. The algorithm is extended to enable variable-length compression, and is compared via numerical results to a related approach based on the information-theoretic technique of multivariate compression.

Original languageEnglish (US)
Title of host publication2016 IEEE International Conference on Communications, ICC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479966646
DOIs
StatePublished - Jul 12 2016
Event2016 IEEE International Conference on Communications, ICC 2016 - Kuala Lumpur, Malaysia
Duration: May 22 2016May 27 2016

Publication series

Name2016 IEEE International Conference on Communications, ICC 2016

Other

Other2016 IEEE International Conference on Communications, ICC 2016
Country/TerritoryMalaysia
CityKuala Lumpur
Period5/22/165/27/16

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

Keywords

  • 5G
  • C-RAN
  • downlink
  • fronthaul
  • quantization

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