Density-Aware, Energy- and Spectrum-Efficient Small Cell Scheduling

Mollahasani, Shahram; Onur, Ertan

doi:10.1109/access.2019.2917722

Cited by 19 publications

(14 citation statements)

References 51 publications

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“…Regardless, a concrete algorithm that can extend to more than two-layer networks is required. A density-aware, energy-efficient, and spectrum-efficient sleep scheduling technique is presented in [147]. The solution is based on BS density adaptation and cell-zooming algorithms.…”

Section: Coverage Planningmentioning

confidence: 99%

Issues, Challenges, and Research Trends in Spectrum Management: A Comprehensive Overview and New Vision for Designing 6G Networks

et al. 2020

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With an extensive growth in user demand for high throughput, large capacity, and low latency, the ongoing deployment of Fifth-Generation (5G) systems is continuously exposing the inherent limitations of the system, as compared with its original premises. Such limitations are encouraging researchers worldwide to focus on next-generation 6G wireless systems, which are expected to address the constraints. To meet the above demands, future radio network architecture should be effectively designed to utilize its maximum radio spectrum capacity. It must simultaneously utilize various new techniques and technologies, such as Carrier Aggregation (CA), Cognitive Radio (CR), and small cell-based Heterogeneous Networks (HetNet), high-spectrum access (mmWave), and Massive Multiple-Input-Multiple-Output (M-MIMO), to achieve the desired results. However, the concurrent operations of these techniques in current 5G cellular networks create several spectrum management issues; thus, a comprehensive overview of these emerging technologies is presented in detail in this study. Then, the problems involved in the concurrent operations of various technologies for the spectrum management of the current 5G network are highlighted. The study aims to provide a detailed review of cooperative communication among all the techniques and potential problems associated with the spectrum management that has been addressed with the possible solutions proposed by the latest researches. Future research challenges are also discussed to highlight the necessary steps that can help achieve the desired objectives for designing 6G wireless networks.

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Section: Coverage Planningmentioning

confidence: 99%

Issues, Challenges, and Research Trends in Spectrum Management: A Comprehensive Overview and New Vision for Designing 6G Networks

et al. 2020

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“…However, with the increased number of SBSs, networks will face other challenges, such as higher energy consumption and interference [6]. Energy efficiency is defined as a main requirement in 5G development, for cost efficiency and sustainable development.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization of Green Small Cell Allocation for IoT Applications in Smart City

Ran

Radwan

2020

IEEE Access

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Small cells (SCs) have proven their marvelous capability, especially dealing with high density of user equipment (UE) in the configuration of Internet of Things (IoT). It is widely accepted that the SCs concept is one of the prospective solutions for 5G networks, specifically targeting IoT, to attain the high demand in the future smart city. SC deployment has attracted the attention of multiple research efforts, due to its importance and potential towards enhancing future networking for IoT. However, there is still a lack of works providing SC allocation with comprehensive optimization modeling, which provides essential infrastructural platform to SC functionalities and services (e.g. offloading). The analysis of the number and positions of SCs, towards the simultaneous optimization of both energy efficiency and data rates, is a highly required research direction. SC allocation facilitates the sustainability and reliability, to support exponentially increasing number of users, as well as yielding feasibility of achieving high traffic demand and low latency performance, in addition to longer sustainability based on enhanced energy efficiency. In this paper, a smart small cell allocation scheme is proposed for IoT in smart city. Integer programming multiobjective optimization problem is formulated, and a new algorithm, based on the fusion of Branch-and-Bound (BnB) and Non-Dominated Sorting Genetic Algorithm II (NSGA-II), is developed. Energy efficiency optimization and data rate maximization are formulated, as mutual objectives to fulfill the key demands of IoT in smart city, based on the estimation of users' behaviors. Simulations are conducted, whose results show that the proposed Smart-SC allocation outperforms the different considered benchmarks, resulting in higher offered data rates, while achieving better energy efficiency.

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“…For example, analysis of Japanese water supply organizations based on network density revealed that the economies of network density existed [23]. The density of the mobile network was perceived, and the base station density adaptive algorithm was designed to improve the throughput of a mobile network [24]. In 2006, a density metric was proposed to measure the complexity of business process models on the basis of a social network [25].…”

Section: Introductionmentioning

confidence: 99%

An Improved Method for Measuring the Complexity in Complex Networks Based on Structure Entropy

2019

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Although structure entropy is a useful method to measure the complexity of complex networks, there exist shortcomings, such as the limits of network scales and network types. By combining structure entropy and the absolute density of network, a method is improved to effectively measure the complexity of complex networks. For the improved measure, not only the topology of network is considered, but also the scales of network are considered, and the measurement of network complexity is not affected by the network scales and types. Moreover, the complexity of small-world networks, BA scale free networks, Sierpinski self-similarity networks, Erodös-Rényi (ER) random networks and six real networks (i.e., the 9/11 terrorist network, Celegans network, a USAir network, the USA Political blogs network, a collaboration network in science of networks (NetScience) and yeast protein interaction (YPI) network) are measured by employing the method. The results show that the improved method is effective and feasible to measure the complexity of complex networks. INDEX TERMS Complex network, structure entropy, absolute density.

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Density-Aware, Energy- and Spectrum-Efficient Small Cell Scheduling

Cited by 19 publications

References 51 publications

Issues, Challenges, and Research Trends in Spectrum Management: A Comprehensive Overview and New Vision for Designing 6G Networks

Issues, Challenges, and Research Trends in Spectrum Management: A Comprehensive Overview and New Vision for Designing 6G Networks

Multi-Objective Optimization of Green Small Cell Allocation for IoT Applications in Smart City

An Improved Method for Measuring the Complexity in Complex Networks Based on Structure Entropy

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