Globally Optimal Energy Efficiency Maximization for Capacity-Limited Fronthaul Crans with Dynamic Power Amplifiers’ Efficiency

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Title: Globally Optimal Energy Efficiency Maximization for Capacity-Limited Fronthaul Crans with Dynamic Power Amplifiers’ Efficiency
Authors: Nguyen, Kien-Giang
Vu, Quang-Doanh
Tran, Le-Nam
Juntti, Markku
Permanent link: http://hdl.handle.net/10197/10384
Date: 13-Sep-2018
Online since: 2019-05-09T10:28:58Z
Abstract: A joint beamforming and remote radio head (RRH)-user association design for downlink of cloud radio access networks (CRANs) is considered. The aim is to maximize the system energy efficiency subject to constraints on users' quality-of-service, capacity offronthaullinks and transmit power. Different to the conventional power consumption models, we embrace the dependence of baseband signal processing power on the data rate, and the dynamics of the power amplifiers' efficiency. The considered problem is a mixed Boolean nonconvex program whose optimal solution is difficult to find. As our main contribution, we provide a discrete branch-reduce-and-bound (DBRnB) approach to solve the problem globally. We also make some modifications to the standard DBRnB procedure. Those remarkably improve the convergence performance. Numerical results are provided to confirm the validity of the proposed method.
Type of material: Conference Publication
Publisher: IEEE
Start page: 3759
End page: 3763
Copyright (published version): 2018 IEEE
Keywords: Energy efficiencyCRANLimited fronthaulNonlinear power amplifierDiscrete branch-reduce-and-bound
DOI: 10.1109/icassp.2018.8461308
Other versions: https://2018.ieeeicassp.org/
Language: en
Status of Item: Not peer reviewed
Is part of: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing: Proceedings
Conference Details: The 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Calgary, Canada, 15-20 April 2018
ISBN: 978-1-5386-4658-8
Appears in Collections:Electrical and Electronic Engineering Research Collection

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