Cell Switch-Off for Networks Deployed With Variable Spatial Regularity

Lagum, Faraj; Le-The, Quoc-Nam; Beitelmal, Tamer; Szyszkowicz, Sebastian S.; Yanıkömeroğlu, Halim

doi:10.1109/lwc.2017.2665472

Cited by 18 publications

(14 citation statements)

References 12 publications

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“…Given a terrestrial network suffering from a temporary high demand for data rate, this chapter 1 considers strategic placement of UAV-BSs to enhance both the capacity and the coverage probability. Inspired by improving the spatial regularity of the BS locations maximizes the coverage probability and the performance of the network [13,23,24,59], we propose an aerial-terrestrial network planning approach that relies on the spatial structure of the network to strategically augment (find the best 3D locations) massive number of UAV-BSs to terrestrial network. We choose the horizontal location of the UAV-BSs such that they improve the spatial regularity of the network's BSs (the T-BSs and the projection of the UAV-BS locations on the ground).…”

Section: Contributionmentioning

confidence: 99%

Stochastic Geometry-Based Tools for Spatial Modeling and Planning of Future Cellular Networks: Opportunistic Cell Switch-off and Strategic Deployment of Flying Base Stations

Lagum¹

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To meet the ever-increasing traffic demand in modern cellular networks, deploying more BSs has imposed is a vital solution. Cellular network (re-)planning is crucial to mitigate the interference and improve the network performance whenever more base stations (BSs) are deployed or some BSs are removed. Realistic spatial modelling for the locations of BSs and accurate quantification for their spatial relationship are prerequisites for effective network planning.In the first part of this thesis, we aim to describe the spatial structure of the BSs using two scalar measures: the density of the BSs and the amount of regularity. We investigate the use of three scalar metrics to measure the spatial relationships among the BSs in cellular networks. We propose a geometry-based scalar metric (the coefficient of variation (CoV) of the length of the corresponding edges of Delaunay triangulation) to quantify the spatial regularity of the repulsive wireless networks. This work develops new approaches for i) mapping between the internal parameters of different point processes commonly used to generate the BS locations, ii) approximating the performance of a repulsive network based on its amount of regularity, and iii) fitting point processes to the spatial deployment of BSs.In the second part, we develop a novel stochastic geometry-based cellular network planning technique that relies on the spatial structure of the network to determine the best deployment or removal locations of the BSs. First, we apply this technique for cell deactivation during the low demand periods. More specifically, cells are switched off so that the remaining active cells are as far away as possible from each other, which maximizes the spatial regularity of the network. The results show significant energy saving and network performance enhancement. Second, we exploit this approach for the strategic densification with UAV-BSs in cellular networks: The deployment of multiple UAV-BSs in the presence of a terrestrial network where the UAV-BSs provide on-demand capacity to the end users. This study provides supply-side estimation for how many UAV-BSs are needed to support a terrestrial network so as to achieve a iii particular quality-of-service and also demonstrate where these UAV-BSs should hover.iv Dedicated to whom this thesis matters most, My parents, Suliman and Saddina, my wife, Nisreen, and my childeren, Suliman and Rose.

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Section: Contributionmentioning

confidence: 99%

Stochastic Geometry-Based Tools for Spatial Modeling and Planning of Future Cellular Networks: Opportunistic Cell Switch-off and Strategic Deployment of Flying Base Stations

Lagum¹

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“…The repulsive point processes (RPPs), from the literature of stochastic geometry, are found to be useful to model actual BS locations. Recent work [55,56] in the context of CSO use RPPs to model BS locations so that they are neither perfect regular nor totally random.…”

Section: Bs Location Models In Cso Literaturementioning

confidence: 99%

“…This problem has been introduced only recently in [55]. Therefore, it is worth evaluating CSO algorithms designed for layouts with irregular BS locations.…”

Section: Bs Location Models In Cso Literaturementioning

confidence: 99%

“…The algorithms terminate when the desired number of active BSs is achieved. The three greedy algorithms were implemented in [55]. While GC and GD result in good performance, SG was found to perform poorly, and hence we excluded it from the discussion.…”

Section: Greedy Algorithmsmentioning

confidence: 99%

“…We place ρM BSs according to a PPP, which is known to give the worst SIR performance [55]: We consider this as the base-line. The algorithms' performance is compared in terms of the SIR gain G SIR (with respect to a PPP deployment).…”

Section: Boundsmentioning

confidence: 99%

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The Cell Switch-Off Approach for Energy Efficient Cellular Networks

Beitelmal¹

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Network densification is a key enabler for providing high data rates and ubiquitous coverage. Although it enables the ambitious target of 1,000-fold gains in capacity, installing more base stations (BSs) challenges the energy efficiency targets of future networks. Cell switch-off (CSO) approaches are proposed to reduce energy consumption in off-peak periods by switching off some BSs. In this thesis, we define an energy-efficient cellular network as one in which as few BSs as possible are switched on while still satisfying all the users demand and quality of service. This thesis contributes to the current state of knowledge by directing the CSO research towards a more realistic, feasible, and practical implementation. We do this by arguing for employing offline (static) CSO and for considering spatially irregular BS deployments. First, we propose a dynamic CSO algorithm based on the well-known set cover problem. Our algorithm outperforms a benchmark algorithm in terms of the total number of switched-off BSs. While dynamic CSO algorithms are designed to adapt to fast changes in demand distribution, proper interference modelling is very challenging. To overcome this challenge, we next study regular static CSO patterns and describe them systematically. We propose sector-based patterns, where not only entire BSs could be switched off (site-based), but their individual sectors too. We compare the performance of different CSO patterns in terms of their energy efficiency and the number of supported users. CSO patterns are advantageous for modelling interference properly, reducing coverage holes, and making the uplink transmissions more energy-efficient for users. Nevertheless, the underlying assumption is that the BSs are deployed according to a regular grid. Finally, we consider spatially irregular BS deployments as a more realistic network model; therefore, we study applying CSO to irregular network layouts with the objective of making the active BS locations as regular as possible. We test the suitability of several algorithms from the p-dispersion problem literature for networks with BSs deployed with variable amounts of regularity. We also demonstrate some of these algorithms on real BS locations.

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Low‐complexity networking based on joint energy efficiency in ultradense mmWave backhaul networks

Tan

Zhao

et al. 2018

Trans Emerging Tel Tech

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As operation cost and energy consumption problems deteriorate with network densification toward 5G, traditional radio resource management and networking strategies must be upgraded. It is observed that when the access network is dealing with a large amount of user traffic, the backhaul (BH) network turns out to be the new bottleneck hindering the cellular system from further increasing its capacity and efficiency. Although wired transmission technologies, such as passive optic fiber networks, are generally available between base stations, the resulting capital expenditure and operational expenditure are prohibitive in an ultradense deployment scenario. To redesign the BH network in 5G, multihop millimeter‐wave transmission is considered as a cost‐efficient and well‐performing candidate. In this paper, we propose a low‐complexity method based on millimeter‐wave transmission to minimize the energy consumption from both the access network and the BH network through joint admission‐power‐traffic control. Concretely, a self‐organizing heuristics is created through which the access and backhaul joint energy efficiency of both the base station and the whole system is maximized under the assumption of predefined user rate requirements. Simulation results show that our proposed method achieves significant reduction (∼95%) in algorithm execution time compared with the branch‐and‐bound search at the expense of little extra energy cost (∼7%). In addition, our proposed method satisfies the quality‐of‐service requirements of user equipment in the system with a lower transmission delay in terms of hops than that of the branch‐and‐bound search. A baseline algorithm called MR‐MPF (maximum reference signal receiver power admission control with minimum power flooding) is also compared to demonstrate our algorithm's superiority in energy saving.

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Cell Switch-Off for Networks Deployed With Variable Spatial Regularity

Cited by 18 publications

References 12 publications

Stochastic Geometry-Based Tools for Spatial Modeling and Planning of Future Cellular Networks: Opportunistic Cell Switch-off and Strategic Deployment of Flying Base Stations

Stochastic Geometry-Based Tools for Spatial Modeling and Planning of Future Cellular Networks: Opportunistic Cell Switch-off and Strategic Deployment of Flying Base Stations

The Cell Switch-Off Approach for Energy Efficient Cellular Networks

Low‐complexity networking based on joint energy efficiency in ultradense mmWave backhaul networks

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