On Optimal Cell Activation for Coverage Preservation in Green Cellular Networks

Chang, Chen‐Yi; Liao, Wanjiun; Hsieh, Hung‐Yun; Shiu, Da-shan

doi:10.1109/tmc.2014.2310227

Cited by 35 publications

(33 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…After that, the traffic load dependent power consumption of SBS is calculated using Equation (10). Then, the power consumption of SBS is obtained using Equation (9). The power consumption due to state switching is calculated using Equation (13).…”

Section: Of 28mentioning

confidence: 99%

“…In the cell zooming scheme, the main objective is to balance the traffic load and increase the energy efficiency of the total network by reducing the energy consumption of BSs. Therefore, BSs with on state should accommodate the coverage hole and cooperate with nearby BSs to deal with the traffic of the turned off BSs [9]. In [10], as an extension of the original cell zooming scheme, the authors proposed an efficient energy saving scheme for BSs, where BSs are turned off when traffic load is very low and active BSs extend the cell coverage by increasing the transmission power.…”

mentioning

confidence: 99%

See 1 more Smart Citation

An Efficient Energy Saving Scheme for Base Stations in 5G Networks with Separated Data and Control Planes Using Particle Swarm Optimization

Kang

Chung

2017

Energies

View full text Add to dashboard Cite

Abstract:Reducing energy consumption of mobile communication networks has gained significant attentions since it takes a major part of the total energy consumption of information and communication technology (ICT). In this paper, we consider 5G networks with heterogeneous macro cells and small cells, where data and control planes are separated. We consider two types of data traffic, i.e., low rate data traffic and high rate data traffic. In basic separation architecture, a macro cell base station (MBS) manages control signals, while a small cell base station (SBS) manages both low rate data traffic and high rate data traffic. In the considered modified separation architecture, an MBS manages control signals and low rate data traffic, while an SBS manages high rate data traffic. Then, an efficient energy saving scheme for base stations (BSs) is proposed, where the state of a BS is determined depending on the number of user equipments (UEs) that request high rate data traffic and the number of UEs that exist under the overlapping areas commonly covered by the considered BS and the neighbor BSs. We formulate an optimization problem for the proposed energy saving scheme and obtain the solution using particle swarm optimization (PSO). Numerical results show that the proposed energy saving scheme in the modified separated network architecture has better energy efficiency compared to the conventional energy saving schemes in both basic and modified separated network architectures. Also, the proposed energy saving scheme has lower aggregate delay.

show abstract

Section: Of 28mentioning

confidence: 99%

mentioning

confidence: 99%

An Efficient Energy Saving Scheme for Base Stations in 5G Networks with Separated Data and Control Planes Using Particle Swarm Optimization

Kang

Chung

2017

Energies

View full text Add to dashboard Cite

show abstract

“…In this technique, macrocells are put into SL and users are offloaded to neighboring macrocells or small cells. The authors in [9] proposed a method for minimizing total power consumption in heterogeneous networks by adaptively switching BSs on/off taking into consideration parameters such as network coverage and the user traffic rates. The work in [10] introduced an SL method for studying the impact of switching off BSs on the capacity and energy efficiency in a homogeneous network of femtocells.…”

Section: Introductionmentioning

confidence: 99%

Interference and Resource Management Through Sleep Mode Selection in Heterogeneous Networks

Ebrahim

Alsusa

2016

IEEE Trans. Commun.

View full text Add to dashboard Cite

Abstract-This paper investigates the capacity and energy consumption metrics of small-cell networks that are enabled with sleep mode (SL) functionality. A novel method is introduced to systematically and accurately identify the potential SL cells that can maximize the spectrum reuse efficiency without the need for an exhaustive search. The performance of the proposed technique is assessed and compared with the always-on approach and an optimal benchmark. The results show that the proposed method significantly outperforms the always-on system and approaches the performance of the optimal benchmark with notably reduced computational burden.

show abstract

“…In [7], the authors proposed a BS turning-off algorithm using the optimal cell coverage that The remainder of this paper is organized as follows. In Section 2, the assumptions of the system model and the problem formulation are presented.…”

Section: Introductionmentioning

confidence: 99%

Green Small Cell Operation of Ultra-Dense Networks Using Device Assistance

Lee

Kim

2016

Energies

View full text Add to dashboard Cite

As higher performance is demanded in 5G networks, energy consumption in wireless networks increases along with the advances of various technologies, so enhancing energy efficiency also becomes an important goal to implement 5G wireless networks. In this paper, we study the energy efficiency maximization problem focused on finding a suitable set of turned-on small cell access points (APs). Finding the suitable on/off states of APs is challenging since the APs can be deployed by users while centralized network planning is not always possible. Therefore, when APs in small cells are randomly deployed and thus redundant in many cases, a mechanism of dynamic AP turning-on/off is required. We propose a device-assisted framework that exploits feedback messages from the user equipment (UE). To solve the problem, we apply an optimization method using belief propagation (BP) on a factor graph. Then, we propose a family of online algorithms inspired by BP, called DANCE, that requires low computational complexity. We perform numerical simulations, and the extensive simulations confirm that BP enhances energy efficiency significantly. Furthermore, simple, but practical DANCE exhibits close performance to BP and also better performance than other popular existing methods. Specifically, in a small-sized network, BP enhances energy efficiency 129%. Furthermore, in ultra-dense networks, DANCE algorithms successfully achieve orders of magnitude higher energy efficiency than that of the baseline.

show abstract

On Optimal Cell Activation for Coverage Preservation in Green Cellular Networks

Cited by 35 publications

References 25 publications

An Efficient Energy Saving Scheme for Base Stations in 5G Networks with Separated Data and Control Planes Using Particle Swarm Optimization

An Efficient Energy Saving Scheme for Base Stations in 5G Networks with Separated Data and Control Planes Using Particle Swarm Optimization

Interference and Resource Management Through Sleep Mode Selection in Heterogeneous Networks

Green Small Cell Operation of Ultra-Dense Networks Using Device Assistance

Contact Info

Product

Resources

About