Green Opportunistic and Efficient Resource Block Allocation Algorithm for LTE Uplink Networks

Kaddour, Fatima Zohra; Vivier, Emmanuelle; Mroueh, Lina; Pischella, Mylène; Martins, Philippe

doi:10.1109/tvt.2014.2365960

Cited by 45 publications

(43 citation statements)

References 14 publications

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“…Studies in [34]- [36] on the other hand investigate EE in conjunction with ICI, albeit, for uplink transmission and therefore focus on UEs EE. In contrast to these studies, our work focuses on EE in the downlink which is the dominant energy consumption factor (and the main contributor to an operators running costs -OPEX) in cellular networks.…”

Section: Introductionmentioning

confidence: 99%

Leveraging Intelligence from Network CDR Data for Interference Aware Energy Consumption Minimization

Zoha

Saeed

Farooq

et al. 2018

IEEE Trans. on Mobile Comput.

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Abstract-Cell densification is being perceived as the panacea for the imminent capacity crunch. However, high aggregated energy consumption and increased inter-cell interference (ICI) caused by densification, remain the two long-standing problems. We propose a novel network orchestration solution for simultaneously minimizing energy consumption and ICI in ultra-dense 5G networks. The proposed solution builds on a big data analysis of over 10 million CDRs from a real network that shows there exists strong spatio-temporal predictability in real network traffic patterns. Leveraging this we develop a novel scheme to pro-actively schedule radio resources and small cell sleep cycles yielding substantial energy savings and reduced ICI, without compromising the users QoS. This scheme is derived by formulating a joint Energy Consumption and ICI minimization problem and solving it through a combination of linear binary integer programming, and progressive analysis based heuristic algorithm. Evaluations using: 1) a HetNet deployment designed for Milan city where big data analytics are used on real CDRs data from the Telecom Italia network to model traffic patterns, 2) NS-3 based Monte-Carlo simulations with synthetic Poisson traffic show that, compared to full frequency reuse and always on approach, in best case, proposed scheme can reduce energy consumption in HetNets to 1/8th while providing same or better QoS.

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Section: Introductionmentioning

confidence: 99%

Leveraging Intelligence from Network CDR Data for Interference Aware Energy Consumption Minimization

Zoha

Saeed

Farooq

et al. 2018

IEEE Trans. on Mobile Comput.

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“…A novel resource allocation scheme has been proposed in the work of Kaddour et al, employing tri‐sectored BSs. The RB allocation is performed in an opportunistic and efficient manner, improving throughput, EE, and user battery lifetime.…”

Section: Related Workmentioning

confidence: 99%

E2ARC: Energy‐efficient adaptive resource block allocation with low complexity in device‐to‐device communication

Gandotra

Jha

Jain

2018

Trans Emerging Tel Tech

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The massive spread of the smart devices demanding high data rate and delay‐sensitized applications has escalated energy consumption levels in the fifth‐generation (5G) wireless communication networks (WCNs). It thus becomes imperative for the mobile network operators to meet the tremendous subscriber demands using energy‐efficient techniques. The limited battery capacities of the mobile terminals (MTs) further make energy efficiency (EE) critical. Device‐to‐device (D2D) communication ensues to be a key enabler technology in the realization of an energy‐efficient 5G WCN. It also serves as a paramount technology for green communication. This paper studies a resource allocation scheme, which iteratively accentuates adaptive reuse of resource blocks (RBs) from the active cellular users to the D2D pairs in a tri‐sectored cell. The cellular users involved in RB allocation to pairs are termed as active. Required count of RBs for each D2D pair is chosen by employing the hidden Markov model. The RB reuse strategy favors enhancement in throughput. The proposed energy‐efficient adaptive RB allocation with low complexity (E2ARC) scheme aims to guarantee ample RBs to individual D2D pairs to optimize the power consumption levels. With advanced throughput and optimal power, augmentation in EE is achieved with a high degree of fairness. E2ARC also comprehends low complexity. The efficacy of the proposed scheme is demonstrated by the simulation results.

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“…Kaddour et al [26] proposed the opportunistic and efficient RB (Radio Block) allocation (OEA) algorithm and QoS (Quality of Service) based OEA, to allocate radio blocks for UEs (User Equipments) in LTE uplink networks. This was proposed with the aim of maximizing the aggregate throughput of UEs, while reducing the transmission power via power control adjustment with respect to the expected QoS of users and radio channel conditions.…”

Section: Multiple User Accessmentioning

confidence: 99%

Survey of wireless big data

Qian

Zhu

Zhang

2017

J. Commun. Inf. Netw.

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Wireless big data describes a wide range of massive data that is generated, collected and stored in wireless networks by wireless devices and users. While these data share some common properties with traditional big data, they have their own unique characteristics and provide numerous advantages for academic research and practical applications. This article reviews the recent advances and trends in the field of wireless big data. Due to space constraints, this survey is not intended to cover all aspects in this field, but to focus on the data aided transmission, data driven network optimization and novel applications. It is expected that the survey will help the readers to understand this exciting and emerging research field better. Moreover, open issues and promising future directions are also identified.

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Green Opportunistic and Efficient Resource Block Allocation Algorithm for LTE Uplink Networks

Cited by 45 publications

References 14 publications

Leveraging Intelligence from Network CDR Data for Interference Aware Energy Consumption Minimization

Leveraging Intelligence from Network CDR Data for Interference Aware Energy Consumption Minimization

E2ARC: Energy‐efficient adaptive resource block allocation with low complexity in device‐to‐device communication

Survey of wireless big data

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