Traffic‐aware two‐dimensional dynamic network provisioning for energy‐efficient cellular systems

Hossain, Md. Farhad; Munasinghe, Kumudu S.; Jamalipour, Abbas

doi:10.1002/ett.2872

Cited by 5 publications

(2 citation statements)

References 47 publications

(102 reference statements)

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“…The traffic volume on weekends and holidays are higher than on weekdays. The behavior of traffic pattern is dependent on daily, weekly and accidental variations [26].…”

Section: Energy Saving Techniquesmentioning

confidence: 99%

Comparison of Energy Efficiency Between Macro and Micro Base Stations Using Energy Saving Strategy

Dahal¹,

Shrestha

Shakya

2020

J. Inst. Engineering

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To meet the subscribers ever increasing traffic demand, micro and macro base stations are being deployed excessively. As the traffic pattern varies according to the user's behavior, the deployment of micro and macro base stations plays a vital role in saving energy while maintaining the traffic demand of the subscribers. A macro base station consumes more than double the energy than a micro base station. Due to the space and time characteristics of the traffic, the BS cannot allocate resources effectively, which results in wasting energy consumption and low energy efficiency. Therefore, energy saving through deployment of base stations play a significant role to increase the energy efficiency. In this paper, the user traffic pattern is determined and the resources needed to fulfill the traffic are analyzed and finally the deployment strategies for the base stations are formulated. Since the base stations are fully loaded only for few hours a day, energy saving on the stations during low traffic will be significant. The energy saving schemes saved up to 18.8 % of energy in macro and 26.9 % of energy in micro BS. So, it would be more efficient to implement a heterogeneous network with more micro cells with energy saving schemes than just macro base stations.

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“…The traffic volume on weekends and holidays are higher than on weekdays. The behavior of traffic pattern is dependent on daily, weekly and accidental variations [26].…”

Section: Energy Saving Techniquesmentioning

confidence: 99%

Comparison of Energy Efficiency Between Macro and Micro Base Stations Using Energy Saving Strategy

Dahal¹,

Shrestha

Shakya

2020

J. Inst. Engineering

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“…Traffic aware network energy management is considered in to preserve power consumption. Authors in investigate two sleep mode algorithms, the first algorithm is dynamic sleep mode and the second one is semi‐static sleep mode.…”

Section: Introductionmentioning

confidence: 99%

Wireless network power optimisation using relay stations blossoming and withering technique

Al-Samawi

Sali

Nissirat

et al. 2015

Trans. Emerging Tel. Tech.

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Power consumption of wireless network is increasing as the demands in wireless data rates are escalating in modern life. Base stations are the major power consumption component in the wireless network. Therefore, the main challenge is to reduce the total power consumed in the network while maintaining the network coverage and its capacity. In this paper, a new relay switching perspective is introduced for relay blossoming and withering algorithm. First, relay switching is considered as a function of time representing the rate of active relays. The effect of the rate of active relays, arrival rate and average load factor of relays on the total network power consumption is modelled. It is found that the rate of active relay function that optimises the network power consumption obeys linear first‐order ordinary differential equation. The effect of different synthesised arrival rate profiles on the rate of active relay is presented. Moreover, relative relay to base station capacity parameter is defined, and its effect on the power optimisation is investigated. Based on the solutions of the ordinary differential equation, an approximate fuzzy‐based relay sleeping mode is introduced. The fuzzy logic sleeping mode utilises the arrival rate and its derivative as inputs. The solution of the differential equations shows that power saving up to 45 and 30 per cent can be achieved in sleeping and idling modes, respectively, in contrast to 42 per cent achieved from the fuzzy sleeping mode. The increasing slope of the arrival rate results in less power saving. Copyright © 2015 John Wiley & Sons, Ltd.

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A generic buffer occupancy expression for stop-and-wait hybrid automatic repeat request protocol over unstable channels

et al. 2015

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Traffic‐aware two‐dimensional dynamic network provisioning for energy‐efficient cellular systems

Cited by 5 publications

References 47 publications

Comparison of Energy Efficiency Between Macro and Micro Base Stations Using Energy Saving Strategy

Comparison of Energy Efficiency Between Macro and Micro Base Stations Using Energy Saving Strategy

Wireless network power optimisation using relay stations blossoming and withering technique

A generic buffer occupancy expression for stop-and-wait hybrid automatic repeat request protocol over unstable channels

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