A Theoretical Performance Bound for Joint Beamformer Design of Wireless Fronthaul and Access Links in Downlink C-RAN

Kadan F. E., Yilmaz A. Ö.

IEEE Transactions on Wireless Communications, vol.21, no.4, pp.2177-2192, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 21 Issue: 4
  • Publication Date: 2022
  • Doi Number: 10.1109/twc.2021.3109837
  • Journal Name: IEEE Transactions on Wireless Communications
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, Civil Engineering Abstracts
  • Page Numbers: pp.2177-2192
  • Keywords: Wireless communication, Signal to noise ratio, Optimization, Interference, Array signal processing, Channel estimation, Standards, Beamforming, C-RAN, performance bound, semi-definite relaxation, wireless fronthaul, CLOUD, MIMO, NETWORKS, TRANSMISSION, OPTIMIZATION
  • Middle East Technical University Affiliated: Yes


IEEEIt is known that data rates in standard cellular networks are limited due to inter-cell interference. An effective solution to this problem is to use the multi-cell cooperation idea. In Cloud Radio Access Network (C-RAN), which is a candidate solution in 5G and future communication networks, cooperation is applied by means of central processors (CPs) connected to simple remote radio heads with finite capacity fronthaul links. In this study, we consider a downlink C-RAN with a wireless fronthaul and aim to minimize total power spent by jointly designing beamformers for fronthaul and access links. We consider the case where perfect channel state information is not available in the CP. We first derive a novel theoretical performance bound for the problem defined. Then we propose four algorithms with different complexities to show the tightness of the bound. The first two algorithms apply successive convex optimizations with semi-definite relaxation ideas where the other two are adapted from well-known beamforming design methods. The detailed simulations under realistic channel conditions show that as the complexity of the algorithm increases, the corresponding performance becomes closer to the bound.