Designing Green C-RAN with limited fronthaul via mixed-integer second order cone programming

This paper considers the downlink transmission of cloud-radio access networks with limited fronthaul capacity constraint. Unlike the existing approaches where power of fronthaul is a quadratic or linear function of respective variables, we consider a more practical model where the power consumed by...

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Published in:IEEE International Conference on Communications (2003) pp. 1 - 6
Main Authors: Phuong Luong, Despins, Charles, Gagnon, Francois, Le-Nam Tran
Format: Conference Proceeding
Language:English
Published: IEEE 01.05.2017
Subjects:
Array signal processing
Cloud radio access networks
energy efficiency
Interference
Iterative methods
limited fronthaul
mixed integer second order cone programming
Numerical models
Power demand
Programming
Wireless communication
ISSN:1938-1883
Online Access:Get full text
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Abstract This paper considers the downlink transmission of cloud-radio access networks with limited fronthaul capacity constraint. Unlike the existing approaches where power of fronthaul is a quadratic or linear function of respective variables, we consider a more practical model where the power consumed by fronthaul depends on the rate served by the corresponding remote radio head (RRH). Then, we formulate a joint design of RRH selection, RRH-user association, and transmit beamforming for the problem of energy efficiency maximization. The formulated problem is a mixed-integer nonconvex program, which is generally NP-hard. For this nonconvex program, we leverage successive convex approximation (SCA) method to develop efficient iterative algorithms to find a high performance. Particularly, we iteratively approximate the continuous nonconvex constraints by conic ones so that the problem obtained at each iteration is a mixed-integer second order cone programming (MI-SOCP) for which dedicated solvers are available. To further reduce the computational complexity, an algorithm based on continuous relaxation and post-processing is proposed. Results show that our proposed algorithms converge faster and outperform known solutions.
AbstractList This paper considers the downlink transmission of cloud-radio access networks with limited fronthaul capacity constraint. Unlike the existing approaches where power of fronthaul is a quadratic or linear function of respective variables, we consider a more practical model where the power consumed by fronthaul depends on the rate served by the corresponding remote radio head (RRH). Then, we formulate a joint design of RRH selection, RRH-user association, and transmit beamforming for the problem of energy efficiency maximization. The formulated problem is a mixed-integer nonconvex program, which is generally NP-hard. For this nonconvex program, we leverage successive convex approximation (SCA) method to develop efficient iterative algorithms to find a high performance. Particularly, we iteratively approximate the continuous nonconvex constraints by conic ones so that the problem obtained at each iteration is a mixed-integer second order cone programming (MI-SOCP) for which dedicated solvers are available. To further reduce the computational complexity, an algorithm based on continuous relaxation and post-processing is proposed. Results show that our proposed algorithms converge faster and outperform known solutions.
Author Despins, Charles
Le-Nam Tran
Gagnon, Francois
Phuong Luong
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  surname: Phuong Luong
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  givenname: Charles
  surname: Despins
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  givenname: Francois
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  surname: Le-Nam Tran
  fullname: Le-Nam Tran
  email: lenam.tran@nuim.ie
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Snippet This paper considers the downlink transmission of cloud-radio access networks with limited fronthaul capacity constraint. Unlike the existing approaches where...
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SubjectTerms Array signal processing
Cloud radio access networks
energy efficiency
Interference
Iterative methods
limited fronthaul
mixed integer second order cone programming
Numerical models
Power demand
Programming
Wireless communication
Title Designing Green C-RAN with limited fronthaul via mixed-integer second order cone programming
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