Optimal Control of Sleep Periods for Wireless Terminals

Azad, Amar Prakash; Alouf, Sara; Altman, Eitan; Borkar, Vivek S.; Paschos, Georgios S.

doi:10.1109/jsac.2011.110910

Cited by 31 publications

(36 citation statements)

References 24 publications

(39 reference statements)

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“…In Ref. 2, based on trade-o® between energy and tra±c, an operation mechanism for the base station is proposed and a greedy algorithm is proposed which improves the energy e±ciency via enabling certain base stations to switch between on and o® states. However, in Ref.…”

Section: Literature Reviewmentioning

confidence: 99%

A Load-Balancing Energy Consumption Minimization Scheme in 5G Heterogeneous Small Cell Wireless Networks Under Coverage Probability Analysis

Xiao

Chen

et al. 2017

Int. J. Patt. Recogn. Artif. Intell.

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Heterogeneous small cell networks (HSCN), as a promising paradigm to increase end-user data rates and improve the overall capacity, is expected to be a key cellular architecture in 5G wireless networks. However, energy consumed in HSCN is considerable due to the massive use of small cells. In this paper, we investigate the energy consumption issue which stems from the enormous number of running small cell base stations (SBSs) deploying in the HSCN. We¯rst propose power consumption models so as to characterize the active state and the idle state of SBSs, respectively. Then two sleep modes for SBSs tier, i.e. random sleep mode and load-awareness dynamic sleep mode, are proposed. The random sleep is designed based on a binomial distribution of the SBS operation probability. Through the analysis on activeness of SBSs, we de¯ne the operation probability for the SBS applying the proposed dynamic sleep mode is associated to its tra±c load level. The closed-form expressions of success probability for coverage, which is used to decide whether an active user can connect to a SBS successfully, are derived for the proposed sleep modes. Energy consumption minimizations are presented for the two proposed sleep modes under the success probability constraint. Simulation results prove the e®ectiveness of the proposed two sleep modes. Di®erent energy saving gains can be achieved via using of the energy saving strategy. ‡ ‡ Corresponding author. This is an Open Access article published by World Scienti¯c Publishing Company. It is distributed under the terms of the Creative Commons Attribution 4.0 (CC-BY) License. Further distribution of this work is permitted, provided the original work is properly cited. The superior of the dynamic sleep mode by comparing the random sleep is also veri¯ed in terms of energy consumption, success probability and power e±ciency.

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Section: Literature Reviewmentioning

confidence: 99%

A Load-Balancing Energy Consumption Minimization Scheme in 5G Heterogeneous Small Cell Wireless Networks Under Coverage Probability Analysis

Xiao

Chen

et al. 2017

Int. J. Patt. Recogn. Artif. Intell.

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“…The objective of our system is presented as (1). s , t are the number of RBs and TTIs in our system, respectively.…”

Section: System Model and Problem Formulationmentioning

confidence: 99%

“…3, we consider a situation of two spaces with equal length. 1 E , 2 E denote the energy of space1 and space2 separately. ' 1 E and ' 2 E are the energy of the two spaces after the directional water-filling algorithm.…”

Section: B the Second Water-filling Levelmentioning

confidence: 99%

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Two levels water-filling scheme for energy saving in LTE system

Niu

Gong

et al. 2013

2013 5th IEEE International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications

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Energy saving plays a significant role in the communication system. Moreover the traffics of 3GPP are expanding and getting ever more complex. We can save more energy by taking advantage of the fact that different traffics have different QoS requirements. This paper proposes a model for such kind of optimization problems. However, it is difficult to find the optimal solution. So in the view of engineering, we propose a scheme, Two Levels Water-Filling Scheme (TLWFS), to improve the energy efficiency while guaranteeing the QoS requirements. In TLWFS, firstly, we classify the traffics into two categories, which are Rate Constrained Traffic (RCT) and Rate NonConstrained traffic (RNCT). Secondly, at the first waterfilling level, the high SNR Resource Blocks (RBs) are selected to guarantee the RCT, with traditional waterfilling algorithm. Finally, at the second water-filling level, the energy and RBs left are used to transfer the RNCT, with directional water-filling algorithm. Numerical results indicate that the TLWFS works well in LTE system, with the energy consumption decreased by 10% with TLWFS, compared to traditional power allocation scheme.

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“…On-off switching of the MT radio interface is adopted at a bursty/low call traffic load to achieve energy saving [7]- [13]. At a continuous/ high call traffic load, energy efficient radio resource allocation is employed [14]- [20].…”

Section: Introductionmentioning

confidence: 99%

Uplink Decentralized Joint Bandwidth and Power Allocation for Energy-Efficient Operation in a Heterogeneous Wireless Medium

Ismail

Gamage

Zhuang

et al. 2015

IEEE Trans. Commun.

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In this paper, energy efficient uplink communications are investigated for battery-constrained mobile terminals (MTs) with service quality requirements and multi-homing capabilities. A heterogeneous wireless medium is considered, where MTs communicate with base stations (BSs) and access points (APs) of different networks with overlapped coverage. Different from the existing works, we develop a quality of service (QoS)-based optimization framework for joint uplink bandwidth and power allocation to maximize energy efficiency for a set of MTs with multi-homing capabilities. The proposed framework is implemented in a decentralized architecture, through coordination among BSs/APs of different networks and MTs, which is a desirable feature when different networks are operated by different service providers. A suboptimal framework is presented with a reduced computational complexity as compared with the optimal framework. Simulation results demonstrate the improved performance of both the optimal and suboptimal frameworks over a state-of-the-art benchmark.Index Terms-Energy efficient communications, green communications, multi-homing resource allocation, heterogeneous wireless medium.

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Optimal Control of Sleep Periods for Wireless Terminals

Cited by 31 publications

References 24 publications

A Load-Balancing Energy Consumption Minimization Scheme in 5G Heterogeneous Small Cell Wireless Networks Under Coverage Probability Analysis

A Load-Balancing Energy Consumption Minimization Scheme in 5G Heterogeneous Small Cell Wireless Networks Under Coverage Probability Analysis

Two levels water-filling scheme for energy saving in LTE system

Uplink Decentralized Joint Bandwidth and Power Allocation for Energy-Efficient Operation in a Heterogeneous Wireless Medium

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