A Hybrid Energy Sharing Framework for Green Cellular Networks

Farooq, Muhammad Junaid; Ghazzai, Hakim; Kadri, Abdullah; ElSawy, Hesham; Alouini, Mohamed‐Slim

doi:10.1109/tcomm.2016.2637917

Cited by 75 publications

(57 citation statements)

References 36 publications

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“…Several works have investigated the framework of SGPCNs [20]- [23] and the applicable resource allocation algorithms [24]- [30]. More specifically, resource allocation algorithms in SGPCNs can be classified into three categories: one-shot algorithms, offline algorithms and online algorithms.…”

Section: A Related Work and Motivationsmentioning

confidence: 99%

“…such that the constraints in (15) are satisfied. Now, we prove the inequalities in (23). Based on (49), we obtain that the nonnegative queue backlogs of access queues and processing queues satisfy lim sup…”

mentioning

confidence: 94%

“…Therefore, we establish the first inequality in (23). Based on the arguments in [37], when the random sources in X are stationary over different slots, there exists an optimal solutionỸ * Ỹ * (t k ) ∀t k ,k to the R-LTGEE minimization problem (54) that almost-surely satisfies: 1)Ỹ * (t k ) is a function of current random sources X (t k ); and 2)Ỹ * (t k ) guarantees thatν m,n ≤ E X r m,n Ỹ * (t k ) ≤s m,n and…”

mentioning

confidence: 99%

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Cross-Layer Scheduling and Beamforming in Smart-Grid Powered Cellular Networks With Heterogeneous Energy Coordination

Dong

Hossain

Cheng

et al. 2020

IEEE Trans. Commun.

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User scheduling, beamforming and energy coordination are investigated in smart-grid powered cellular networks (SGPCNs), where the base stations are powered by a smart grid and natural renewable energy sources. Heterogeneous energy coordination is considered in SGPCNs, namely energy merchandizing with the smart grid and energy exchanging among the base stations. A long-term grid-energy expenditure minimization problem with proportional-rate constraints is formulated for SGPCNs. Since user scheduling is coupled with the beamforming vectors, the formulated problem is challenging to handle via standard convex optimization methods. In practice, the beamforming vectors need to be updated over each slot according to the channel variations. User scheduling needs to be updated over several slots (frame) since the frequent scheduling of user equipment can cause reliability issues. Therefore, the Lyapunov optimization method is used to decouple the problem. A practical two-scale algorithm is proposed to schedule users at each frame, and obtain the beamforming vectors and amount of exchanged natural renewable energy at each slot. We prove that the proposed two-scale algorithm can asymptotically achieve the optimal solutions via tuning a control parameter. Numerical results verify the performance of the proposed twoscale algorithm. NOMENCLATURE Variables DefinitionsM Number of BSTs L Number of antennas at each BST N m Number of associated UEs in the mth BST T Number of slots in each frame T k Set of slots in the kth frame h m,n (t k ) Channel-coefficient vector of the (m, n)th access link ω m,n Pathloss of the (m, n)th access link a m,n [k] Scheduled UE indicator y m,n (t k ) Received signal of the (m, n)th UE ).w m,n (t k ) Single-stream beamforming vector for the (m, n)th UE z m,n (t k ) AWGN at the (m, n)th UE σ 2 m,n Power of the AWGN at the (m, n)th UE SINR m,n Received SINR of the (m, n)th UE

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Section: A Related Work and Motivationsmentioning

confidence: 99%

mentioning

confidence: 94%

mentioning

confidence: 99%

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Cross-Layer Scheduling and Beamforming in Smart-Grid Powered Cellular Networks With Heterogeneous Energy Coordination

Dong

Hossain

Cheng

et al. 2020

IEEE Trans. Commun.

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“…With the two-way energy trading between the smart grid and SCNs, incorporating the natural renewable energy (NRE) into the SCNs becomes an ecologically-and economically-friendly solution to cut down the energy bills. Due to the volatility of NRE arrival, several research efforts have been made in the design of smart grid powered cellular communication frameworks [8], [9] and algorithms [10]- [13]. For example, the authors in [10] investigated the impact of volatility of NRE arrival on the packet rates.…”

Section: Introductionmentioning

confidence: 99%

Cross-Layer Scheduling and Beamforming in Smart Grid Powered Small-Cell Networks

Hossain

Cheng

Leung

et al. 2019

ICC 2019 - 2019 IEEE International Conference on Communications (ICC)

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In the small-cell networks (SCNs) with multiple small-cell base stations (ScBSs), the joint design of beamforming vectors, user scheduling and ScBS sleeping is investigated with the constraints on proportional rate. A long-term gridenergy expenditure minimization problem is formulated for the considered SCNs, which are powered by the smart grid and natural renewable energy. Since the scheduled user indicators are coupled with the beamforming vectors, the formulated problem is challenging to handle. In order to decouple the beamforming vectors from the scheduled user indicators, the Lyapunov optimization technique is used. As a result, a practical two-scale algorithm is proposed to allocate the user scheduling indicators and ScBS sleeping variables at the coarse-grained granularity (frame) as well as obtain the beamforming vectors at the fine-grained granularity (slot). Numerical results are used to verify the performance of the proposed two-scale algorithm.

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“…Hence, the BSs powered by RE sources may sometimes have an excess of energy while at other times, they may be energy deficient. Hence, handling this uncertainty in the energy management framework for cellular networks presents an important challenge that has received interests in literature [14], [21]- [24]. The authors of [23], [24], for instance, have employed stochastic programming for adaptive power management under various uncertainties including renewable power generation.…”

Section: Introductionmentioning

confidence: 99%

Energy Management Optimization for Cellular Networks Under Renewable Energy Generation Uncertainty

Rached

Ghazzai

Kadri

et al. 2017

IEEE Trans. on Green Commun. Netw.

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Abstract-The integration of renewable energy (RE) as an alternative power source for cellular networks has been deeply investigated in literature. However, RE generation is often assumed to be deterministic; an impractical assumption for realistic scenarios. In this paper, an efficient energy procurement strategy for cellular networks powered simultaneously by the smart grid (SG) and locally deployed RE sources characterized by uncertain processes is proposed. For a one-day operation cycle, the mobile operator aims to reduce its total energy cost by optimizing the amounts of energy to be procured from the local RE sources and SG at each time period. Additionally, it aims to determine the amount of extra generated RE to be sold back to SG. A chance constrained optimization is first proposed to deal with the RE generation uncertainty. Then, two convex approximation approaches: Chernoff and Chebyshev methods, characterized by different levels of knowledge about the RE generation, are developed to determine the energy procurement strategy for different risk levels. In addition, their performances are analyzed for various daily scenarios through selected simulation results. It is shown that the higher complex Chernoff method outperforms the Chebyshev one for different risk levels set by the operator.

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A Hybrid Energy Sharing Framework for Green Cellular Networks

Cited by 75 publications

References 36 publications

Cross-Layer Scheduling and Beamforming in Smart-Grid Powered Cellular Networks With Heterogeneous Energy Coordination

Cross-Layer Scheduling and Beamforming in Smart-Grid Powered Cellular Networks With Heterogeneous Energy Coordination

Cross-Layer Scheduling and Beamforming in Smart Grid Powered Small-Cell Networks

Energy Management Optimization for Cellular Networks Under Renewable Energy Generation Uncertainty

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