Cell throughput based sleep control scheme for heterogeneous cellular networks

Phaiwitthayaphorn, Prapassorn; Boonsrimuang, Pisit; Reangsuntea, Pongsathorn; Fujii, Takashi; Sanada, Kosuke; Möri, K.; Kobayashi, Hideo

doi:10.1109/ecticon.2017.8096305

Cited by 7 publications

(17 citation statements)

References 4 publications

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“…The conventional cell throughput based sleep control [11] is a simple but effective scheme applied for the SBS sleeping. The cell capacity ratio, which is a ratio of currently achieved cell throughput to maximum achievable cell throughput, is introduced as decision criteria for making SBSs sleep, in order to find the SBSs with the waste of energy.…”

Section: Conventional Cell Throughput Based Sleep Controlmentioning

confidence: 99%

“…One of the most attractive techniques for reducing power consumption and increasing energy efficiency is to integrate sleep control into SBSs. The existing schemes for SBS sleep control have been proposed, for example: random and repulsive schemes [8], distance-sensitive repulsive sleeping strategy [9], traffic based sleep control scheme [10], cell throughput based sleep control scheme [11], and adaptive SBS sleep control scheme [12]. Although these schemes can reduce power consumption and improve energy efficiency, they could degrade system throughput when compared with the no sleep control system.…”

Section: Introductionmentioning

confidence: 99%

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System Performance Enhancement with Energy Efficiency Based Sleep Control for 5G Heterogeneous Cellular Networks

2022

IJIES

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This paper presents an improved sleep control algorithm for small base stations (SBSs) in 5G New Radio (NR) heterogeneous cellular networks (HetNets). HetNets consist of various base station tiers, including macro base stations (MBSs) and small base stations (SBSs), and have been suggested as a promising solution to enhance wireless coverage and network capacity, employing many SBSs into the MBS coverage. However, power consumption increases significantly as a result of an increase in the number of the SBSs. To solve this problem, the SBS sleep control has been proposed to reduce power consumption for the SBSs and improves energy efficiency, whereas it deteriorates system throughput compared with no sleep control system, consequently degrading the quality of service (QoS) performance at user equipments (UEs). This paper proposes an enhanced algorithm for SBS sleep control based on energy efficiency as a decision criterion for SBS operating state. From the evaluation results through computer simulation, the proposed scheme can provide improved performance for both energy efficiency and system throughput simultaneously, that is it can improve energy efficiency while maintaining almost the same system throughput as the no sleep control system. Concretely, the proposed scheme has the 14.89% improvement in energy efficiency while providing almost the same system throughput of over 99%, compared with no sleep control system.

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Section: Conventional Cell Throughput Based Sleep Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

System Performance Enhancement with Energy Efficiency Based Sleep Control for 5G Heterogeneous Cellular Networks

2022

IJIES

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“…After the allocation of antennae users, the algorithm starts to worry about the sectorization in the BBUs, returning to an allocation of RRHs-BBUs. The parameters used in the model are shown in the table below [19], [20]: As the objective function of the implemented PSO, it was used a combination of KPIs proposed in [4], which were adjusted to the scenario proposed and that shall be described below. Weights were assigned to obtain the maximum QoS, using the PSO.…”

Section: Related Workmentioning

confidence: 99%

Two-Level Allocation for H-CRAN Architecture Based in Offloading

Gonçalves

Leto

Vieira

et al. 2019

J. Microw. Optoelectron. Electromagn. Appl.

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The accelerated data and apps growth represents significant challenges to the next generation of mobile networks. Amongst them, it is highlighted the necessity for a coexistence of new and old patterns during the transition of architectures. Thus, this paper has investigated solutions for offloading into a hybrid architecture, also known as H-CRAN (Heterogeneous Cloud Radio Access Network Architecture), that centralizes processing and searches a better use of the network resources. The strategy of optimization was analyzed through the evolutive algorithm PSO (Particle Swarm Optimization), in order to find a suboptimal solution to the TLA (Two-Level Allocation) in the H-CRAN architecture and another one based on FIFO (First In, First Out), for benchmarking purposes. SNR (Signal-to-noise ratio) average, Maximum Bit Rate, the number of users with or without connections and number of connections in RRHs and macro were used as performance measurements. Through the results, it was noticed an improvement of approximately 60% in the Maximum Bit Rate when compared to the traditional approach, enabling better service to the users.

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“…Assuming that both macro and small-cell base stations may be put into sleep mode, the authors in [20] formulated the optimization problem of resource partitioning and user association to minimize the total energy of the system. To improve the energy efficiency and system throughput of the system in the HetNets, a cell throughput based on sleep control scheme for the small base stations was proposed in [21]. To improve the energy efficiency of the whole system, the authors in [22] proposed an algorithm combining BS sleeping with dynamic clustering (SMDC) to maximize EE.…”

Section: Introductionmentioning

confidence: 99%

Optimized sleep strategy based on clustering in dense heterogeneous networks

Wang

et al. 2018

J Wireless Com Network

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As a large number of small base stations have been deployed in dense heterogeneous networks, the increasing cost of energy has become a challenging issue. In this paper, we propose an optimized clustering-based sleep strategy to release the power consumption and interference in the system. First, we group the small base stations with large interference as a cluster in which the binary particle swarm optimization (BPSO) algorithm is used to formulate a sleep strategy for small base stations in the clusters. Since the small base stations between clusters have less interference, the whole spectrum resources can be shared in all clusters and the orthogonal spectrum resources are allocated for the small base stations in the same cluster. The strategy effectively restrains the co-tier interference in the system. Furthermore, a separate sleep strategy is applied for each cluster to improve the sleep and activation efficiency of the small base stations. The simulation results show that the proposed sleep strategy can improve the satisfaction of user equipment and reduce the power consumption. As the increasing number of user equipment, the outage probability of the system can be reduced effectively.

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Cell throughput based sleep control scheme for heterogeneous cellular networks

Cited by 7 publications

References 4 publications

System Performance Enhancement with Energy Efficiency Based Sleep Control for 5G Heterogeneous Cellular Networks

System Performance Enhancement with Energy Efficiency Based Sleep Control for 5G Heterogeneous Cellular Networks

Two-Level Allocation for H-CRAN Architecture Based in Offloading

Optimized sleep strategy based on clustering in dense heterogeneous networks

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