Dynamic point selection CoMP enabled hybrid powered green cellular networks

Jahid, Abu; Shams, Abdullah Bin; Hossain, Md. Farhad

doi:10.1016/j.compeleceng.2018.03.011

Cited by 21 publications

(13 citation statements)

References 15 publications

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“…Looking at the user population dynamics, we find many approaches that optimize BS operation modes for a specific (fixed) user population [1,11,14,27,34]. Jahid et al [15,16] on the other hand focus on user association specifically and on the use of on-site renewable energy sources (e.g. solar panels), and simply switch any BS into sleep mode during off-peak hours.…”

Section: Discussion and Related Workmentioning

confidence: 99%

“…In short, we use load estimates (12) to obtain a sufficient condition for switching a BS into sleep mode. We use the load estimates (15) to obtain a sufficient condition for activating a BS, resulting in a set of candidate BSs for which a change in operation mode improves the objective. The condition (9) considers changing the operation mode of a single BS at the time.…”

Section: ( ð15þmentioning

confidence: 99%

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A self-organizing base station sleeping and user association strategy for dense cellular networks

2020

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Due to the rising concerns of energy consumption in wireless networks, base station (BS) sleeping strategies were introduced to save energy in low traffic scenarios. In this paper we analyse a weighted trade-off between energy consumption and user-perceived performance in dense cellular networks. We present an optimization problem representing this trade-off and derive properties of its optimal solutions. Using these properties we design a self-organizing strategy that dynamically (online) makes load-aware user association and BS operation decisions. Our strategy is self-organizing in the sense that it does not need any information or optimization beforehand, it simply relies on real-time load measurements at the BSs and user-reported SINR values. We furthermore present extensive simulation results, demonstrating the effectiveness of our self-organizing strategy and the impact of increased energy consumption on the user-perceived performance.

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Section: Discussion and Related Workmentioning

confidence: 99%

Section: ( ð15þmentioning

confidence: 99%

A self-organizing base station sleeping and user association strategy for dense cellular networks

2020

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“…The electrical power produced by WT mainly relies on wind velocity, weather system, and hub height. The amount of electrical power generated by the WT can be calculated by [13], [38]…”

Section: B Wind Generatormentioning

confidence: 99%

Techno-Economic and Energy Efficiency Analysis of Optimal Power Supply Solutions for Green Cellular Base Stations

Jahid

Hossain²,

Monju

et al. 2020

IEEE Access

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The widespread proliferation of internet access, affordable wireless gadgets, the user data demand and the corresponding extended cellular networks entailing significant energy consumption and carbon footprints. With the added benefits of renewable energy harvesting (REH) technology, telecom base stations (BSs) are predominantly supplied by green power sources to reduce operational expenditure (OPEX) and atmospheric pollution with guaranteed quality of service (QoS). Accordingly, this paper examines the plausibility of optimal power supply solutions such as standalone solar photovoltaic (PV), hybrid PV/wind turbine (PV/WT), hybrid PV/diesel generator (DG) and hybrid PV/electric grid (PV/EG) to feed the Long Term Evolution (LTE) BSs pertaining to technical, economic and environmental aspects in Bangladesh. An extensive Monte-Carlo based simulations are performed to evaluate wireless network performance in terms of throughput, energy efficiency (EE), energy efficiency gain (EE gain), average energy savings, radio efficiency varying system bandwidth (B) and BS transmission power (P TX) considering the dynamic behavior of traffic intensity and renewable energy (RE) generation profile. By leveraging the cell zooming technique and a green traffic steering framework endeavors to minimize the net present cost and maximize the average energy savings as well. The simulation results reveal that the cell zooming technique attained energy savings yielding up to 36% and improvement of EE gain achieved about 23% with effective modeling of REH. Subsequently, a comprehensive comparison of the aforementioned schemes is pledged for further validation. INDEX TERMS Green cellular networks, renewable energy harvesting, hybrid energy, energy efficiency, cell zooming, eco-sustainability, LTE.

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“…Some recent works like [11] incorporates energy and cost awareness into similar type of network but data cooperation is not considered. Though the authors of [12] and [13] have improved the EE of the system using data cooperation, energy cooperation is not the main focus of this work. To the best of our knowledge, this is the first work which maximizes the EE of a hybrid-powered HetNet with both data and energy cooperation using a novel combinatorial (subgradient-metaheuristic) optimization technique.…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Joint Power Allocation and Energy Cooperation for Hybrid-Powered Comp-Enabled HetNet

Euttamarajah

Tan

2020

IEEE Access

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Base station (BS) coordination with respect to data and energy cooperation has recently emerged as a potential solution for enhancing the energy efficiency (EE) of multi-cell multi-tier cellular network architecture. This work studies the EE maximization problem in a hybrid-powered (grid and renewable energy source) heterogeneous network (HetNet) where the data and energy are jointly coordinated among the BSs. We propose a combinatorial optimization algorithm to maximize the system EE with the aim to reduce grid power consumption (GPC). Due to the complexity of the formulation, Lagrange dual decomposition and metaheuristic method are incorporated to solve the problem. Furthermore, the nonfractional programming EE problem is solved using the Dinkelbach's method which converges faster with a lower complexity. Simulation results show that cooperation among the BSs to share the channel information and energy reduces the GPC by nearly 20% and increases EE around 10% during harvested energy scarcity among the BSs.

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Dynamic point selection CoMP enabled hybrid powered green cellular networks

Cited by 21 publications

References 15 publications

A self-organizing base station sleeping and user association strategy for dense cellular networks

A self-organizing base station sleeping and user association strategy for dense cellular networks

Techno-Economic and Energy Efficiency Analysis of Optimal Power Supply Solutions for Green Cellular Base Stations

Energy-Efficient Joint Power Allocation and Energy Cooperation for Hybrid-Powered Comp-Enabled HetNet

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