Reducing energy consumption in cellular networks by adjusting transmitted power of base stations

AbstractWith the combination of Mobile Edge Computing (MEC) and the next generation cellular networks, computation requests from end devices can be offloaded promptly and accurately by edge servers equipped on Base Stations (BSs). However, due to the densified heterogeneous deployment of BSs, the end device may be covered by more than one BS, which brings new challenges for offloading decision, that is whether and where to offload computing tasks for low latency and energy cost. This paper formulates a multi-user-to-multi-servers (MUMS) edge computing problem in ultra-dense cellular networks. The MUMS problem is divided and conquered by two phases, which are server selection and offloading decision. For the server selection phases, mobile users are grouped to one BS considering both physical distance and workload. After the grouping, the original problem is divided into parallel multi-user-to-one-server offloading decision subproblems. To get fast and near-optimal solutions for these subproblems, a distributed offloading strategy based on a binary-coded genetic algorithm is designed to get an adaptive offloading decision. Convergence analysis of the genetic algorithm is given and extensive simulations show that the proposed strategy significantly reduces the average latency and energy consumption of mobile devices. Compared with the state-of-the-art offloading researches, our strategy reduces the average delay by 56% and total energy consumption by 14% in the ultra-dense cellular networks.

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Low-Carb: Reducing energy consumption in operational cellular networks

2013 IEEE Global Communications Conference (GLOBECOM) ◽

10.1109/glocom.2013.6831461 ◽

2013 ◽

Author(s):

M. S. Ilyas ◽

G. Baig ◽

M. A. Qureshi ◽

Q. U. A. Nadeem ◽

A. Raza ◽

...

Keyword(s):

Energy Consumption ◽

Cellular Networks ◽

Reducing Energy

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Liquid cell management for reducing energy consumption expenses in hybrid energy powered cellular networks

2014 IEEE Wireless Communications and Networking Conference (WCNC) ◽

10.1109/wcnc.2014.6952474 ◽

2014 ◽

Cited By ~ 3

Author(s):

Heng Wang ◽

Hongjia Li ◽

Xin Chen ◽

Yifang Qin ◽

Lei Yang ◽

...

Keyword(s):

Energy Consumption ◽

Cellular Networks ◽

Hybrid Energy ◽

Liquid Cell ◽

Reducing Energy

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Optimal matching between energy consumption of Base Stations and traffic load in green cellular networks

2012 1st IEEE International Conference on Communications in China (ICCC) ◽

10.1109/iccchina.2012.6356927 ◽

2012 ◽

Cited By ~ 1

Author(s):

Xiaowei Qin ◽

Feng Chen ◽

Guo Wei

Keyword(s):

Energy Consumption ◽

Cellular Networks ◽

Base Stations ◽

Traffic Load ◽

Optimal Matching

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On Reducing Energy Cost Consumption in Heterogeneous Cellular Networks using Optimal Time Constraint Algorithm

10.21203/rs.3.rs-1090831/v1 ◽

2021 ◽

Author(s):

V Kalpana ◽

Divyendu Kumar Mishra ◽

K. Chanthirasekaran ◽

Anandakumar Haldorai ◽

Srigitha. S. Nath ◽

...

Keyword(s):

Renewable Energy ◽

Energy Consumption ◽

Cellular Networks ◽

Energy Cost ◽

Time Constraint ◽

Base Stations ◽

Optimal Time ◽

Energy Usage ◽

Heterogeneous Cellular Networks ◽

A New Technique

Abstract The increasing data demand in recent years has resulted in a considerable rise in heterogeneous cellular network energy usage. Advances in heterogeneous cellular networks with renewable energy supplied from base stations offer the cellular communications sector interesting options. Rising energy consumption, fuelled by huge growth in user count as well as usage of data, has emerged as the most pressing challenge for operators in fulfilling cost-cutting and environmental-impact objectives. The use of minimum power relay stations or base stations in conventional microcells is intended to lower cellular network's total energy usage. We examine the reasons, difficulties, and techniques for addressing the energy cost reduction issue for such renewable heterogeneous networks in this paper. Because of the variety of renewable energy as well as mobile traffic, then the issue related to a reduction in energy cost necessitates both spatial and temporal resource allotment optimization. In this paper, we proposed a new technique for reducing the energy consumption cost using the optimal time constraint algorithmic approach. We demonstrate that the proposed method has time as well as space complexity. Experimental simulations on actual databases with synthetic costs are used to confirm the usefulness and efficacy of our method.

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Game Theoretic Infrastructure Sharing in Wireless Cellular Networks

Game Theory Framework Applied to Wireless Communication Networks - Advances in Wireless Technologies and Telecommunication ◽

10.4018/978-1-4666-8642-7.ch014 ◽

2015 ◽

pp. 368-398

Author(s):

Alexandra Bousia ◽

Elli Kartsakli ◽

Angelos Antonopoulos ◽

Luis Alonso ◽

Christos Verikoukis

Keyword(s):

Energy Consumption ◽

Cellular Networks ◽

Cost Savings ◽

Mobile Network ◽

Cost Effective ◽

Base Stations ◽

Traffic Demand ◽

Game Theoretic ◽

Mobile Network Operators ◽

Low Traffic

The emerging traffic demand has fueled the rapid densification of cellular networks. The increased number of Base Stations (BSs) leads to augmented energy consumption and expenditures for the Mobile Network Operators (MNOs), especially during low traffic, when many of the BSs remain underutilized. Hence, the MNOs are encouraged to provide “green” and cost effective solutions for their networks. In this chapter, an innovative algorithm for infrastructure sharing in two-operator environments is proposed, based on BSs switching off during low traffic periods. Motivated by the conflicting interests of the operators, the problem is formulated in a game theoretic framework that enables the MNOs to act individually to estimate the switching off probabilities that reduce their financial cost. The authors analytically and experimentally estimate the potential energy and cost savings that can be accomplished. The obtained results show a significant reduction in both energy consumption and expenditures, thus giving the operators the necessary incentives for infrastructure sharing.

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Energy-Efficient Wireless Cellular Communications through Network Resource Dynamic Adaptation

International Journal of Business Data Communications and Networking ◽

10.4018/jbdcn.2013040102 ◽

2013 ◽

Vol 9 (2) ◽

pp. 11-26

Author(s):

Josip Lorincz

Keyword(s):

Energy Efficiency ◽

Cellular Networks ◽

Access Network ◽

Base Stations ◽

Dynamic Adaptation ◽

Optimization Approach ◽

Transmitted Power ◽

Network Resources ◽

Network Resource ◽

Traffic Pattern

Cellular networks represent one of the major energy consumers of communication networks and their contribution to the global carbon footprint and energy consumption continuously and rapidly increases. Improving energy efficiency of the cellular access networks become an important requirement and has recently gained considerable attention of the research community and operators. In this paper, improving cellular networks energy efficiency through dynamic adaptation of network resources is presented with foundations which justify practical realization of such approach. Paper gives insight into how the traffic pattern variations and transmitted power scaling influence on the instantaneous power consumption of the base stations. Also, impact of the base stations Tx power on two prominent energy efficiency metrics of the cellular access network is discussed. Results of a proposed optimization approach which is based on dynamic adaptation of the base stations on/off activity and the transmitted power in accordance with the spatial and temporal variations of traffic are presented. According to obtained results, dynamic adaptation of network resources can offer significant monthly energy savings on the level of complete cellular access network.

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