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Semidynamic Green Resource Management in Downlink Heterogeneous Networks by Group Sparse Power Control

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Semidynamic Green Resource Management in Downlink Heterogeneous Networks by Group Sparse Power Control. / Cao, Pan; Liu, Wenjia; Thompson, John; Yang, Chenyang; Jorswieck, Eduard.

In: IEEE Journal of Selected Areas in Communications, Vol. 34, No. 5, 31.05.2016, p. 1250-1266.

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Cao, Pan ; Liu, Wenjia ; Thompson, John ; Yang, Chenyang ; Jorswieck, Eduard. / Semidynamic Green Resource Management in Downlink Heterogeneous Networks by Group Sparse Power Control. In: IEEE Journal of Selected Areas in Communications. 2016 ; Vol. 34, No. 5. pp. 1250-1266.

Bibtex

@article{ce700adfade846d1bb78f30585c07fb8,
title = "Semidynamic Green Resource Management in Downlink Heterogeneous Networks by Group Sparse Power Control",
abstract = "This paper addresses an energy-saving problem for the downlink of a cloud-assisted heterogeneous network (HetNet) using a time-division duplex (TDD) model, which aims to minimize the base stations (BSs) sum power consumption while meeting the rate requirement of each user equipment (UE). The basic idea of this work is to make use of the scalability of system configurations such that green resource management can be employed by flexibly switching off some unnecessary hardware components, especially for off-peak traffic scenarios. This motivates us to utilize a flexible BS power consumption formulation to jointly model its signal processing and circuit power, transmit power, and backhaul transmission power. Instead of using the integer variables [1,0] to control the “on/off” two status of a BS in most previous work, we employ the group sparsity of a transmit power vector to denote the activity of each frequency carrier (FC) such that the signal processing and circuit power can be scaled with the effective bandwidth, thereby leading to multiple sleep modes for a BS in multi-FC systems. Based on this BS power model and the group sparsity concept, a simplified resource allocation scheme for joint BS-UE association, FC assignment, downlink power allocation, and BS sleep modes determination is presented, which is based on the average channel statistics computed over the coherence time of the large scale fading (LSF). This semidynamic green resource management mechanism can be formulated as a NP-hard optimization problem. In order to make it tractable, the successive convex approximation (SCA)-based algorithm is applied to efficiently find a stationary solution using a cloud-based centralized optimization. Simulation results also verify the effectiveness of the proposed mechanism under the developed BS power consumption model.",
author = "Pan Cao and Wenjia Liu and John Thompson and Chenyang Yang and Eduard Jorswieck",
note = "Pan Cao, Wnjia Liu, John S. Thompson, Chenyang Yang, and Eduard A. Jorswieck, 'Semidynamic Green Resource Management in Downlink Heterogeneous Networks by Group Sparse Power Control', IEEE Journal on Selected Areas in Communications, Vol. 34 (5): 1250-1266, May 2016, doi: https://doi.org/10.1109/JSAC.2016.2545478. ",
year = "2016",
month = may,
day = "31",
doi = "10.1109/JSAC.2016.2545478",
language = "English",
volume = "34",
pages = "1250--1266",
journal = "IEEE Journal of Selected Areas in Communications",
issn = "0733-8716",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "5",

}

RIS

TY - JOUR

T1 - Semidynamic Green Resource Management in Downlink Heterogeneous Networks by Group Sparse Power Control

AU - Cao, Pan

AU - Liu, Wenjia

AU - Thompson, John

AU - Yang, Chenyang

AU - Jorswieck, Eduard

N1 - Pan Cao, Wnjia Liu, John S. Thompson, Chenyang Yang, and Eduard A. Jorswieck, 'Semidynamic Green Resource Management in Downlink Heterogeneous Networks by Group Sparse Power Control', IEEE Journal on Selected Areas in Communications, Vol. 34 (5): 1250-1266, May 2016, doi: https://doi.org/10.1109/JSAC.2016.2545478.

PY - 2016/5/31

Y1 - 2016/5/31

N2 - This paper addresses an energy-saving problem for the downlink of a cloud-assisted heterogeneous network (HetNet) using a time-division duplex (TDD) model, which aims to minimize the base stations (BSs) sum power consumption while meeting the rate requirement of each user equipment (UE). The basic idea of this work is to make use of the scalability of system configurations such that green resource management can be employed by flexibly switching off some unnecessary hardware components, especially for off-peak traffic scenarios. This motivates us to utilize a flexible BS power consumption formulation to jointly model its signal processing and circuit power, transmit power, and backhaul transmission power. Instead of using the integer variables [1,0] to control the “on/off” two status of a BS in most previous work, we employ the group sparsity of a transmit power vector to denote the activity of each frequency carrier (FC) such that the signal processing and circuit power can be scaled with the effective bandwidth, thereby leading to multiple sleep modes for a BS in multi-FC systems. Based on this BS power model and the group sparsity concept, a simplified resource allocation scheme for joint BS-UE association, FC assignment, downlink power allocation, and BS sleep modes determination is presented, which is based on the average channel statistics computed over the coherence time of the large scale fading (LSF). This semidynamic green resource management mechanism can be formulated as a NP-hard optimization problem. In order to make it tractable, the successive convex approximation (SCA)-based algorithm is applied to efficiently find a stationary solution using a cloud-based centralized optimization. Simulation results also verify the effectiveness of the proposed mechanism under the developed BS power consumption model.

AB - This paper addresses an energy-saving problem for the downlink of a cloud-assisted heterogeneous network (HetNet) using a time-division duplex (TDD) model, which aims to minimize the base stations (BSs) sum power consumption while meeting the rate requirement of each user equipment (UE). The basic idea of this work is to make use of the scalability of system configurations such that green resource management can be employed by flexibly switching off some unnecessary hardware components, especially for off-peak traffic scenarios. This motivates us to utilize a flexible BS power consumption formulation to jointly model its signal processing and circuit power, transmit power, and backhaul transmission power. Instead of using the integer variables [1,0] to control the “on/off” two status of a BS in most previous work, we employ the group sparsity of a transmit power vector to denote the activity of each frequency carrier (FC) such that the signal processing and circuit power can be scaled with the effective bandwidth, thereby leading to multiple sleep modes for a BS in multi-FC systems. Based on this BS power model and the group sparsity concept, a simplified resource allocation scheme for joint BS-UE association, FC assignment, downlink power allocation, and BS sleep modes determination is presented, which is based on the average channel statistics computed over the coherence time of the large scale fading (LSF). This semidynamic green resource management mechanism can be formulated as a NP-hard optimization problem. In order to make it tractable, the successive convex approximation (SCA)-based algorithm is applied to efficiently find a stationary solution using a cloud-based centralized optimization. Simulation results also verify the effectiveness of the proposed mechanism under the developed BS power consumption model.

U2 - 10.1109/JSAC.2016.2545478

DO - 10.1109/JSAC.2016.2545478

M3 - Article

VL - 34

SP - 1250

EP - 1266

JO - IEEE Journal of Selected Areas in Communications

JF - IEEE Journal of Selected Areas in Communications

SN - 0733-8716

IS - 5

ER -