Energy Efficiency Maximization for C-RANs: Discrete Monotonic Optimization, Penalty, and ℓ0-Approximation Methods

Files in This Item:
File Description SizeFormat 
Giang_TSP_Final_manuscript.pdf381.65 kBAdobe PDFDownload
Title: Energy Efficiency Maximization for C-RANs: Discrete Monotonic Optimization, Penalty, and ℓ0-Approximation Methods
Authors: Nguyen, Kien-Giang
Vu, Quang-Doanh
Juntti, Markku
Tran, Le-Nam
Permanent link: http://hdl.handle.net/10197/10540
Date: 25-Jun-2018
Online since: 2019-05-20T12:48:21Z
Abstract: We study downlink of multiantenna cloud radio access networks with finite-capacity fronthaul links. The aim is to propose joint designs of beamforming and remote radio head (RRH)-user association, subject to constraints on users' quality-of-service, limited capacity of fronthaul links and transmit power, to maximize the system energy efficiency. To cope with the limited-capacity fronthaul we consider the problem of RRH-user association to select a subset of users that can be served by each RRH. Moreover, different to the conventional power consumption models, we take into account the dependence of the baseband signal processing power on the data rate, as well as the dynamics of the efficiency of power amplifiers. The considered problem leads to a mixed binary integer program which is difficult to solve. Our first contribution is to derive a globally optimal solution for the considered problem by customizing a discrete branch-reduce-and-bound approach. Since the global optimization method requires a high computational effort, we further propose two suboptimal solutions able to achieve the near optimal performance but with much reduced complexity. To this end, we transform the design problem into continuous (but inherently nonconvex) programs by two approaches: penalty and l 0 -approximation methods. These resulting continuous nonconvex problems are then solved by the successive convex approximation framework. Numerical results are provided to evaluate the effectiveness of the proposed approaches.
Funding Details: Science Foundation Ireland
Type of material: Journal Article
Publisher: IEEE
Journal: IEEE Transactions on Signal Processing
Volume: 66
Issue: 17
Start page: 4435
End page: 4449
Copyright (published version): 2018 IEEE
Keywords: Energy efficiencyCloud radio access networkLimited fronthaul capacityRate-dependent signal processing powerNonlinear power amplifierBeamformingMixed binary integer programDiscrete branch-reduce-and-boundSuccessive convex approximation
DOI: 10.1109/tsp.2018.2849746
Language: en
Status of Item: Peer reviewed
Conference Details: Also presented at: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2018), Alberta, Canada, April 15-20 2018
Appears in Collections:Electrical and Electronic Engineering Research Collection

Show full item record

Google ScholarTM

Check

Altmetric


This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. For other possible restrictions on use please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.