Joint Beamforming and Clustering for Energy Efficient Multi-Cloud Radio Access Networks

Robert-Jeron Reifert, Alaa Alameer Ahmad, Hayssam Dahrouj, Anas Chaaban, Aydin Sezgin, Tareq Y. Al-Naffouri, Mohamed-Slim Alouini

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

2 Scopus citations


The tremendous growth of data traffic in mobile communication networks (MCNs) and the associated exponential increase in mobile devices’ numbers necessitate the use of multi-cloud radio access networks (MC-RANs) as a viable solution to cope with the requirements of next-generation MCNs (6G). In MC-RANs, each central processor (CP) manages the signal processing of its own set of base stations (BSs), and so the system performance becomes a function of the joint intra-cloud and inter-cloud interference mitigation techniques. To this end, this paper considers the problem of maximizing the network-wide energy efficiency (EE) subject to user-to-cloud association, fronthaul capacity, maximum transmit power, and achievable rate constraints, so as to determine the joint beamforming vector of each user and the user-to-cloud association strategy. The paper tackles the non-convex and mixed discrete-continuous nature of the problem formulation using fractional programming (FP) and inner-convex approximation (ICA) techniques, as well as l 0 -norm relaxation heuristics, and shows how the proposed approach can be implemented in a distributed fashion via a reasonable amount of information exchange across the CPs. The paper simulations highlight the appreciable algorithmic efficiency of the proposed approach over state-of-the-art schemes.
Original languageEnglish (US)
Title of host publication2022 IEEE Wireless Communications and Networking Conference (WCNC)
StatePublished - May 16 2022

Bibliographical note

KAUST Repository Item: Exported on 2022-05-19
Acknowledgements: The work of R.-J. Reifert, A. A. Ahmad, and A. Sezgin was funded by the Federal Ministry of Education and Research (BMBF) of the Federal Republic of Germany (Forderkennzeichen 01IS18063A, ReMiX). ¨ The work of H. Dahrouj is supported by the Center of Excellence for NEOM Research at KAUST.


Dive into the research topics of 'Joint Beamforming and Clustering for Energy Efficient Multi-Cloud Radio Access Networks'. Together they form a unique fingerprint.

Cite this